Merge branch 'main' into pr-713

2026-02-18 04:58:59 +00:00 · 2026-02-18 04:58:59 +00:00 · 5c61f30546
commit 5c61f30546
parent 8f49b52079 4c577761e2
24 changed files with 1235 additions and 225 deletions
--- a/README.md
+++ b/README.md
@ -16,12 +16,16 @@

 ⚡️ Delivers core agent functionality in just **~4,000** lines of code — **99% smaller** than Clawdbot's 430k+ lines.

-📏 Real-time line count: **3,536 lines** (run `bash core_agent_lines.sh` to verify anytime)
+📏 Real-time line count: **3,696 lines** (run `bash core_agent_lines.sh` to verify anytime)

 ## 📢 News

+- **2026-02-16** 🦞 nanobot now integrates a [ClawHub](https://clawhub.ai) skill — search and install public agent skills.
+- **2026-02-15** 🔑 nanobot now supports OpenAI Codex provider with OAuth login support.
+- **2026-02-14** 🔌 nanobot now supports MCP! See [MCP section](#mcp-model-context-protocol) for details.
 - **2026-02-13** 🎉 Released v0.1.3.post7 — includes security hardening and multiple improvements. All users are recommended to upgrade to the latest version. See [release notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.3.post7) for more details.
 - **2026-02-12** 🧠 Redesigned memory system — Less code, more reliable. Join the [discussion](https://github.com/HKUDS/nanobot/discussions/566) about it!
+- **2026-02-11** ✨ Enhanced CLI experience and added MiniMax support!
 - **2026-02-10** 🎉 Released v0.1.3.post6 with improvements! Check the updates [notes](https://github.com/HKUDS/nanobot/releases/tag/v0.1.3.post6) and our [roadmap](https://github.com/HKUDS/nanobot/discussions/431).
 - **2026-02-09** 💬 Added Slack, Email, and QQ support — nanobot now supports multiple chat platforms!
 - **2026-02-08** 🔧 Refactored Providers—adding a new LLM provider now takes just 2 simple steps! Check [here](#providers).
@ -107,14 +111,22 @@ nanobot onboard

 **2. Configure** (`~/.nanobot/config.json`)

-For OpenRouter - recommended for global users:
+Add or merge these **two parts** into your config (other options have defaults).
+
+*Set your API key* (e.g. OpenRouter, recommended for global users):
 ```json
 {
  "providers": {
    "openrouter": {
      "apiKey": "sk-or-v1-xxx"
    }
-  },
+  }
+}
+```
+
+*Set your model*:
+```json
+{
  "agents": {
    "defaults": {
      "model": "anthropic/claude-opus-4-5"
@ -126,63 +138,26 @@ For OpenRouter - recommended for global users:
 **3. Chat**

 ```bash
-nanobot agent -m "What is 2+2?"
+nanobot agent
 ```

 That's it! You have a working AI assistant in 2 minutes.

-## 🖥️ Local Models (vLLM)
-
-Run nanobot with your own local models using vLLM or any OpenAI-compatible server.
-
-**1. Start your vLLM server**
-
-```bash
-vllm serve meta-llama/Llama-3.1-8B-Instruct --port 8000
-```
-
-**2. Configure** (`~/.nanobot/config.json`)
-
-```json
-{
-  "providers": {
-    "vllm": {
-      "apiKey": "dummy",
-      "apiBase": "http://localhost:8000/v1"
-    }
-  },
-  "agents": {
-    "defaults": {
-      "model": "meta-llama/Llama-3.1-8B-Instruct"
-    }
-  }
-}
-```
-
-**3. Chat**
-
-```bash
-nanobot agent -m "Hello from my local LLM!"
-```
-
-> [!TIP]
-> The `apiKey` can be any non-empty string for local servers that don't require authentication.
-
 ## 💬 Chat Apps

-Talk to your nanobot through Telegram, Discord, WhatsApp, Feishu, Mochat, DingTalk, Slack, Email, or QQ — anytime, anywhere.
+Connect nanobot to your favorite chat platform.

-| Channel | Setup |
-|---------|-------|
-| **Telegram** | Easy (just a token) |
-| **Discord** | Easy (bot token + intents) |
-| **WhatsApp** | Medium (scan QR) |
-| **Feishu** | Medium (app credentials) |
-| **Mochat** | Medium (claw token + websocket) |
-| **DingTalk** | Medium (app credentials) |
-| **Slack** | Medium (bot + app tokens) |
-| **Email** | Medium (IMAP/SMTP credentials) |
-| **QQ** | Easy (app credentials) |
+| Channel | What you need |
+|---------|---------------|
+| **Telegram** | Bot token from @BotFather |
+| **Discord** | Bot token + Message Content intent |
+| **WhatsApp** | QR code scan |
+| **Feishu** | App ID + App Secret |
+| **Mochat** | Claw token (auto-setup available) |
+| **DingTalk** | App Key + App Secret |
+| **Slack** | Bot token + App-Level token |
+| **Email** | IMAP/SMTP credentials |
+| **QQ** | App ID + App Secret |

 <details>
 <summary><b>Telegram</b> (Recommended)</summary>
@ -599,6 +574,7 @@ Config file: `~/.nanobot/config.json`

 | Provider | Purpose | Get API Key |
 |----------|---------|-------------|
+| `custom` | Any OpenAI-compatible endpoint (direct, no LiteLLM) | — |
 | `openrouter` | LLM (recommended, access to all models) | [openrouter.ai](https://openrouter.ai) |
 | `anthropic` | LLM (Claude direct) | [console.anthropic.com](https://console.anthropic.com) |
 | `openai` | LLM (GPT direct) | [platform.openai.com](https://platform.openai.com) |
@ -607,10 +583,105 @@ Config file: `~/.nanobot/config.json`
 | `gemini` | LLM (Gemini direct) | [aistudio.google.com](https://aistudio.google.com) |
 | `minimax` | LLM (MiniMax direct) | [platform.minimax.io](https://platform.minimax.io) |
 | `aihubmix` | LLM (API gateway, access to all models) | [aihubmix.com](https://aihubmix.com) |
+| `siliconflow` | LLM (SiliconFlow/硅基流动, API gateway) | [siliconflow.cn](https://siliconflow.cn) |
 | `dashscope` | LLM (Qwen) | [dashscope.console.aliyun.com](https://dashscope.console.aliyun.com) |
 | `moonshot` | LLM (Moonshot/Kimi) | [platform.moonshot.cn](https://platform.moonshot.cn) |
 | `zhipu` | LLM (Zhipu GLM) | [open.bigmodel.cn](https://open.bigmodel.cn) |
 | `vllm` | LLM (local, any OpenAI-compatible server) | — |
+| `openai_codex` | LLM (Codex, OAuth) | `nanobot provider login openai-codex` |
+| `github_copilot` | LLM (GitHub Copilot, OAuth) | `nanobot provider login github-copilot` |
+
+<details>
+<summary><b>OpenAI Codex (OAuth)</b></summary>
+
+Codex uses OAuth instead of API keys. Requires a ChatGPT Plus or Pro account.
+
+**1. Login:**
+```bash
+nanobot provider login openai-codex
+```
+
+**2. Set model** (merge into `~/.nanobot/config.json`):
+```json
+{
+  "agents": {
+    "defaults": {
+      "model": "openai-codex/gpt-5.1-codex"
+    }
+  }
+}
+```
+
+**3. Chat:**
+```bash
+nanobot agent -m "Hello!"
+```
+
+> Docker users: use `docker run -it` for interactive OAuth login.
+
+</details>
+
+<details>
+<summary><b>Custom Provider (Any OpenAI-compatible API)</b></summary>
+
+Connects directly to any OpenAI-compatible endpoint — LM Studio, llama.cpp, Together AI, Fireworks, Azure OpenAI, or any self-hosted server. Bypasses LiteLLM; model name is passed as-is.
+
+```json
+{
+  "providers": {
+    "custom": {
+      "apiKey": "your-api-key",
+      "apiBase": "https://api.your-provider.com/v1"
+    }
+  },
+  "agents": {
+    "defaults": {
+      "model": "your-model-name"
+    }
+  }
+}
+```
+
+> For local servers that don't require a key, set `apiKey` to any non-empty string (e.g. `"no-key"`).
+
+</details>
+
+<details>
+<summary><b>vLLM (local / OpenAI-compatible)</b></summary>
+
+Run your own model with vLLM or any OpenAI-compatible server, then add to config:
+
+**1. Start the server** (example):
+```bash
+vllm serve meta-llama/Llama-3.1-8B-Instruct --port 8000
+```
+
+**2. Add to config** (partial — merge into `~/.nanobot/config.json`):
+
+*Provider (key can be any non-empty string for local):*
+```json
+{
+  "providers": {
+    "vllm": {
+      "apiKey": "dummy",
+      "apiBase": "http://localhost:8000/v1"
+    }
+  }
+}
+```
+
+*Model:*
+```json
+{
+  "agents": {
+    "defaults": {
+      "model": "meta-llama/Llama-3.1-8B-Instruct"
+    }
+  }
+}
+```
+
+</details>

 <details>
 <summary><b>Adding a New Provider (Developer Guide)</b></summary>
@ -657,8 +728,43 @@ That's it! Environment variables, model prefixing, config matching, and `nanobot
 </details>


+### MCP (Model Context Protocol)
+
+> [!TIP]
+> The config format is compatible with Claude Desktop / Cursor. You can copy MCP server configs directly from any MCP server's README.
+
+nanobot supports [MCP](https://modelcontextprotocol.io/) — connect external tool servers and use them as native agent tools.
+
+Add MCP servers to your `config.json`:
+
+```json
+{
+  "tools": {
+    "mcpServers": {
+      "filesystem": {
+        "command": "npx",
+        "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir"]
+      }
+    }
+  }
+}
+```
+
+Two transport modes are supported:
+
+| Mode | Config | Example |
+|------|--------|---------|
+| **Stdio** | `command` + `args` | Local process via `npx` / `uvx` |
+| **HTTP** | `url` | Remote endpoint (`https://mcp.example.com/sse`) |
+
+MCP tools are automatically discovered and registered on startup. The LLM can use them alongside built-in tools — no extra configuration needed.
+
+
+
+
 ### Security

+> [!TIP]
 > For production deployments, set `"restrictToWorkspace": true` in your config to sandbox the agent.

 | Option | Default | Description |
@ -678,6 +784,7 @@ That's it! Environment variables, model prefixing, config matching, and `nanobot
 | `nanobot agent --logs` | Show runtime logs during chat |
 | `nanobot gateway` | Start the gateway |
 | `nanobot status` | Show status |
+| `nanobot provider login openai-codex` | OAuth login for providers |
 | `nanobot channels login` | Link WhatsApp (scan QR) |
 | `nanobot channels status` | Show channel status |

@ -705,7 +812,21 @@ nanobot cron remove <job_id>
 > [!TIP]
 > The `-v ~/.nanobot:/root/.nanobot` flag mounts your local config directory into the container, so your config and workspace persist across container restarts.

-Build and run nanobot in a container:
+### Docker Compose
+
+```bash
+docker compose run --rm nanobot-cli onboard   # first-time setup
+vim ~/.nanobot/config.json                     # add API keys
+docker compose up -d nanobot-gateway           # start gateway
+```
+
+```bash
+docker compose run --rm nanobot-cli agent -m "Hello!"   # run CLI
+docker compose logs -f nanobot-gateway                   # view logs
+docker compose down                                      # stop
+```
+
+### Docker

 ```bash
 # Build the image
@ -753,7 +874,6 @@ PRs welcome! The codebase is intentionally small and readable. 🤗

 **Roadmap** — Pick an item and [open a PR](https://github.com/HKUDS/nanobot/pulls)!

- [x] **Voice Transcription** — Support for Groq Whisper (Issue #13)
 - [ ] **Multi-modal** — See and hear (images, voice, video)
 - [ ] **Long-term memory** — Never forget important context
 - [ ] **Better reasoning** — Multi-step planning and reflection
--- a/SECURITY.md
+++ b/SECURITY.md
@ -5,7 +5,7 @@
 If you discover a security vulnerability in nanobot, please report it by:

 1. **DO NOT** open a public GitHub issue
-2. Create a private security advisory on GitHub or contact the repository maintainers
+2. Create a private security advisory on GitHub or contact the repository maintainers (xubinrencs@gmail.com)
 3. Include:
   - Description of the vulnerability
   - Steps to reproduce
--- a/docker-compose.yml
+++ b/docker-compose.yml
@ -0,0 +1,31 @@
+x-common-config: &common-config
+  build:
+    context: .
+    dockerfile: Dockerfile
+  volumes:
+    - ~/.nanobot:/root/.nanobot
+
+services:
+  nanobot-gateway:
+    container_name: nanobot-gateway
+    <<: *common-config
+    command: ["gateway"]
+    restart: unless-stopped
+    ports:
+      - 18790:18790
+    deploy:
+      resources:
+        limits:
+          cpus: '1'
+          memory: 1G
+        reservations:
+          cpus: '0.25'
+          memory: 256M
+  
+  nanobot-cli:
+    <<: *common-config
+    profiles:
+      - cli
+    command: ["status"]
+    stdin_open: true
+    tty: true
--- a/nanobot/agent/context.py
+++ b/nanobot/agent/context.py
@ -225,12 +225,16 @@ To recall past events, grep {workspace_path}/memory/HISTORY.md"""
        Returns:
            Updated message list.
        """
-        msg: dict[str, Any] = {"role": "assistant", "content": content or ""}
+        msg: dict[str, Any] = {"role": "assistant"}
+
+        # Omit empty content — some backends reject empty text blocks
+        if content:
+            msg["content"] = content

        if tool_calls:
            msg["tool_calls"] = tool_calls

-        # Thinking models reject history without this
+        # Include reasoning content when provided (required by some thinking models)
        if reasoning_content:
            msg["reasoning_content"] = reasoning_content

--- a/nanobot/agent/loop.py
+++ b/nanobot/agent/loop.py
@ -1,7 +1,9 @@
 """Agent loop: the core processing engine."""

 import asyncio
+from contextlib import AsyncExitStack
 import json
+import json_repair
 from pathlib import Path
 from typing import Any

@ -50,6 +52,7 @@ class AgentLoop:
        cron_service: "CronService | None" = None,
        restrict_to_workspace: bool = False,
        session_manager: SessionManager | None = None,
+        mcp_servers: dict | None = None,
    ):
        from nanobot.config.schema import ExecToolConfig
        from nanobot.cron.service import CronService
@ -82,6 +85,9 @@ class AgentLoop:
        )
        
        self._running = False
+        self._mcp_servers = mcp_servers or {}
+        self._mcp_stack: AsyncExitStack | None = None
+        self._mcp_connected = False
        self._register_default_tools()
    
    def _register_default_tools(self) -> None:
@ -116,6 +122,16 @@ class AgentLoop:
        if self.cron_service:
            self.tools.register(CronTool(self.cron_service))
    
+    async def _connect_mcp(self) -> None:
+        """Connect to configured MCP servers (one-time, lazy)."""
+        if self._mcp_connected or not self._mcp_servers:
+            return
+        self._mcp_connected = True
+        from nanobot.agent.tools.mcp import connect_mcp_servers
+        self._mcp_stack = AsyncExitStack()
+        await self._mcp_stack.__aenter__()
+        await connect_mcp_servers(self._mcp_servers, self.tools, self._mcp_stack)
+
    def _set_tool_context(self, channel: str, chat_id: str) -> None:
        """Update context for all tools that need routing info."""
        if message_tool := self.tools.get("message"):
@ -191,6 +207,7 @@ class AgentLoop:
    async def run(self) -> None:
        """Run the agent loop, processing messages from the bus."""
        self._running = True
+        await self._connect_mcp()
        logger.info("Agent loop started")

        while self._running:
@ -213,6 +230,15 @@ class AgentLoop:
            except asyncio.TimeoutError:
                continue
    
+    async def close_mcp(self) -> None:
+        """Close MCP connections."""
+        if self._mcp_stack:
+            try:
+                await self._mcp_stack.aclose()
+            except (RuntimeError, BaseExceptionGroup):
+                pass  # MCP SDK cancel scope cleanup is noisy but harmless
+            self._mcp_stack = None
+
    def stop(self) -> None:
        """Stop the agent loop."""
        self._running = False
@ -395,9 +421,15 @@ Respond with ONLY valid JSON, no markdown fences."""
                model=self.model,
            )
            text = (response.content or "").strip()
+            if not text:
+                logger.warning("Memory consolidation: LLM returned empty response, skipping")
+                return
            if text.startswith("```"):
                text = text.split("\n", 1)[-1].rsplit("```", 1)[0].strip()
-            result = json.loads(text)
+            result = json_repair.loads(text)
+            if not isinstance(result, dict):
+                logger.warning(f"Memory consolidation: unexpected response type, skipping. Response: {text[:200]}")
+                return

            if entry := result.get("history_entry"):
                memory.append_history(entry)
@ -432,6 +464,7 @@ Respond with ONLY valid JSON, no markdown fences."""
        Returns:
            The agent's response.
        """
+        await self._connect_mcp()
        msg = InboundMessage(
            channel=channel,
            sender_id="user",
--- a/nanobot/agent/skills.py
+++ b/nanobot/agent/skills.py
@ -167,10 +167,10 @@ class SkillsLoader:
        return content
    
    def _parse_nanobot_metadata(self, raw: str) -> dict:
-        """Parse nanobot metadata JSON from frontmatter."""
+        """Parse skill metadata JSON from frontmatter (supports nanobot and openclaw keys)."""
        try:
            data = json.loads(raw)
-            return data.get("nanobot", {}) if isinstance(data, dict) else {}
+            return data.get("nanobot", data.get("openclaw", {})) if isinstance(data, dict) else {}
        except (json.JSONDecodeError, TypeError):
            return {}
    
--- a/nanobot/agent/tools/cron.py
+++ b/nanobot/agent/tools/cron.py
@ -50,6 +50,10 @@ class CronTool(Tool):
                    "type": "string",
                    "description": "Cron expression like '0 9 * * *' (for scheduled tasks)"
                },
+                "tz": {
+                    "type": "string",
+                    "description": "IANA timezone for cron expressions (e.g. 'America/Vancouver')"
+                },
                "at": {
                    "type": "string",
                    "description": "ISO datetime for one-time execution (e.g. '2026-02-12T10:30:00')"
@ -68,30 +72,46 @@ class CronTool(Tool):
        message: str = "",
        every_seconds: int | None = None,
        cron_expr: str | None = None,
+        tz: str | None = None,
        at: str | None = None,
        job_id: str | None = None,
        **kwargs: Any
    ) -> str:
        if action == "add":
-            return self._add_job(message, every_seconds, cron_expr, at)
+            return self._add_job(message, every_seconds, cron_expr, tz, at)
        elif action == "list":
            return self._list_jobs()
        elif action == "remove":
            return self._remove_job(job_id)
        return f"Unknown action: {action}"
    
-    def _add_job(self, message: str, every_seconds: int | None, cron_expr: str | None, at: str | None) -> str:
+    def _add_job(
+        self,
+        message: str,
+        every_seconds: int | None,
+        cron_expr: str | None,
+        tz: str | None,
+        at: str | None,
+    ) -> str:
        if not message:
            return "Error: message is required for add"
        if not self._channel or not self._chat_id:
            return "Error: no session context (channel/chat_id)"
+        if tz and not cron_expr:
+            return "Error: tz can only be used with cron_expr"
+        if tz:
+            from zoneinfo import ZoneInfo
+            try:
+                ZoneInfo(tz)
+            except (KeyError, Exception):
+                return f"Error: unknown timezone '{tz}'"
        
        # Build schedule
        delete_after = False
        if every_seconds:
            schedule = CronSchedule(kind="every", every_ms=every_seconds * 1000)
        elif cron_expr:
-            schedule = CronSchedule(kind="cron", expr=cron_expr)
+            schedule = CronSchedule(kind="cron", expr=cron_expr, tz=tz)
        elif at:
            from datetime import datetime
            dt = datetime.fromisoformat(at)
--- a/nanobot/agent/tools/mcp.py
+++ b/nanobot/agent/tools/mcp.py
@ -0,0 +1,80 @@
+"""MCP client: connects to MCP servers and wraps their tools as native nanobot tools."""
+
+from contextlib import AsyncExitStack
+from typing import Any
+
+from loguru import logger
+
+from nanobot.agent.tools.base import Tool
+from nanobot.agent.tools.registry import ToolRegistry
+
+
+class MCPToolWrapper(Tool):
+    """Wraps a single MCP server tool as a nanobot Tool."""
+
+    def __init__(self, session, server_name: str, tool_def):
+        self._session = session
+        self._original_name = tool_def.name
+        self._name = f"mcp_{server_name}_{tool_def.name}"
+        self._description = tool_def.description or tool_def.name
+        self._parameters = tool_def.inputSchema or {"type": "object", "properties": {}}
+
+    @property
+    def name(self) -> str:
+        return self._name
+
+    @property
+    def description(self) -> str:
+        return self._description
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return self._parameters
+
+    async def execute(self, **kwargs: Any) -> str:
+        from mcp import types
+        result = await self._session.call_tool(self._original_name, arguments=kwargs)
+        parts = []
+        for block in result.content:
+            if isinstance(block, types.TextContent):
+                parts.append(block.text)
+            else:
+                parts.append(str(block))
+        return "\n".join(parts) or "(no output)"
+
+
+async def connect_mcp_servers(
+    mcp_servers: dict, registry: ToolRegistry, stack: AsyncExitStack
+) -> None:
+    """Connect to configured MCP servers and register their tools."""
+    from mcp import ClientSession, StdioServerParameters
+    from mcp.client.stdio import stdio_client
+
+    for name, cfg in mcp_servers.items():
+        try:
+            if cfg.command:
+                params = StdioServerParameters(
+                    command=cfg.command, args=cfg.args, env=cfg.env or None
+                )
+                read, write = await stack.enter_async_context(stdio_client(params))
+            elif cfg.url:
+                from mcp.client.streamable_http import streamable_http_client
+                read, write, _ = await stack.enter_async_context(
+                    streamable_http_client(cfg.url)
+                )
+            else:
+                logger.warning(f"MCP server '{name}': no command or url configured, skipping")
+                continue
+
+            session = await stack.enter_async_context(ClientSession(read, write))
+            await session.initialize()
+
+            tools = await session.list_tools()
+            for tool_def in tools.tools:
+                wrapper = MCPToolWrapper(session, name, tool_def)
+                registry.register(wrapper)
+                logger.debug(f"MCP: registered tool '{wrapper.name}' from server '{name}'")
+
+            logger.info(f"MCP server '{name}': connected, {len(tools.tools)} tools registered")
+        except Exception as e:
+            logger.error(f"MCP server '{name}': failed to connect: {e}")
--- a/nanobot/agent/tools/message.py
+++ b/nanobot/agent/tools/message.py
@ -52,6 +52,11 @@ class MessageTool(Tool):
                "chat_id": {
                    "type": "string",
                    "description": "Optional: target chat/user ID"
+                },
+                "media": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "description": "Optional: list of file paths to attach (images, audio, documents)"
                }
            },
            "required": ["content"]
@ -62,6 +67,7 @@ class MessageTool(Tool):
        content: str, 
        channel: str | None = None, 
        chat_id: str | None = None,
+        media: list[str] | None = None,
        **kwargs: Any
    ) -> str:
        channel = channel or self._default_channel
@ -76,11 +82,13 @@ class MessageTool(Tool):
        msg = OutboundMessage(
            channel=channel,
            chat_id=chat_id,
-            content=content
+            content=content,
+            media=media or []
        )
        
        try:
            await self._send_callback(msg)
-            return f"Message sent to {channel}:{chat_id}"
+            media_info = f" with {len(media)} attachments" if media else ""
+            return f"Message sent to {channel}:{chat_id}{media_info}"
        except Exception as e:
            return f"Error sending message: {str(e)}"
--- a/nanobot/channels/slack.py
+++ b/nanobot/channels/slack.py
@ -10,6 +10,8 @@ from slack_sdk.socket_mode.request import SocketModeRequest
 from slack_sdk.socket_mode.response import SocketModeResponse
 from slack_sdk.web.async_client import AsyncWebClient

+from slackify_markdown import slackify_markdown
+
 from nanobot.bus.events import OutboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
@ -84,7 +86,7 @@ class SlackChannel(BaseChannel):
            use_thread = thread_ts and channel_type != "im"
            await self._web_client.chat_postMessage(
                channel=msg.chat_id,
-                text=msg.content or "",
+                text=self._to_mrkdwn(msg.content),
                thread_ts=thread_ts if use_thread else None,
            )
        except Exception as e:
@ -150,13 +152,15 @@ class SlackChannel(BaseChannel):

        text = self._strip_bot_mention(text)

-        thread_ts = event.get("thread_ts") or event.get("ts")
+        thread_ts = event.get("thread_ts")
+        if self.config.reply_in_thread and not thread_ts:
+            thread_ts = event.get("ts")
        # Add :eyes: reaction to the triggering message (best-effort)
        try:
            if self._web_client and event.get("ts"):
                await self._web_client.reactions_add(
                    channel=chat_id,
-                    name="eyes",
+                    name=self.config.react_emoji,
                    timestamp=event.get("ts"),
                )
        except Exception as e:
@ -203,3 +207,31 @@ class SlackChannel(BaseChannel):
        if not text or not self._bot_user_id:
            return text
        return re.sub(rf"<@{re.escape(self._bot_user_id)}>\s*", "", text).strip()
+
+    _TABLE_RE = re.compile(r"(?m)^\|.*\|$(?:\n\|[\s:|-]*\|$)(?:\n\|.*\|$)*")
+
+    @classmethod
+    def _to_mrkdwn(cls, text: str) -> str:
+        """Convert Markdown to Slack mrkdwn, including tables."""
+        if not text:
+            return ""
+        text = cls._TABLE_RE.sub(cls._convert_table, text)
+        return slackify_markdown(text)
+
+    @staticmethod
+    def _convert_table(match: re.Match) -> str:
+        """Convert a Markdown table to a Slack-readable list."""
+        lines = [ln.strip() for ln in match.group(0).strip().splitlines() if ln.strip()]
+        if len(lines) < 2:
+            return match.group(0)
+        headers = [h.strip() for h in lines[0].strip("|").split("|")]
+        start = 2 if re.fullmatch(r"[|\s:\-]+", lines[1]) else 1
+        rows: list[str] = []
+        for line in lines[start:]:
+            cells = [c.strip() for c in line.strip("|").split("|")]
+            cells = (cells + [""] * len(headers))[: len(headers)]
+            parts = [f"**{headers[i]}**: {cells[i]}" for i in range(len(headers)) if cells[i]]
+            if parts:
+                rows.append(" · ".join(parts))
+        return "\n".join(rows)
+
--- a/nanobot/channels/telegram.py
+++ b/nanobot/channels/telegram.py
@ -78,6 +78,26 @@ def _markdown_to_telegram_html(text: str) -> str:
    return text


+def _split_message(content: str, max_len: int = 4000) -> list[str]:
+    """Split content into chunks within max_len, preferring line breaks."""
+    if len(content) <= max_len:
+        return [content]
+    chunks: list[str] = []
+    while content:
+        if len(content) <= max_len:
+            chunks.append(content)
+            break
+        cut = content[:max_len]
+        pos = cut.rfind('\n')
+        if pos == -1:
+            pos = cut.rfind(' ')
+        if pos == -1:
+            pos = max_len
+        chunks.append(content[:pos])
+        content = content[pos:].lstrip()
+    return chunks
+
+
 class TelegramChannel(BaseChannel):
    """
    Telegram channel using long polling.
@ -178,35 +198,59 @@ class TelegramChannel(BaseChannel):
            await self._app.shutdown()
            self._app = None
    
+    @staticmethod
+    def _get_media_type(path: str) -> str:
+        """Guess media type from file extension."""
+        ext = path.rsplit(".", 1)[-1].lower() if "." in path else ""
+        if ext in ("jpg", "jpeg", "png", "gif", "webp"):
+            return "photo"
+        if ext == "ogg":
+            return "voice"
+        if ext in ("mp3", "m4a", "wav", "aac"):
+            return "audio"
+        return "document"
+
    async def send(self, msg: OutboundMessage) -> None:
        """Send a message through Telegram."""
        if not self._app:
            logger.warning("Telegram bot not running")
            return

-        # Stop typing indicator for this chat
        self._stop_typing(msg.chat_id)

        try:
-            # chat_id should be the Telegram chat ID (integer)
            chat_id = int(msg.chat_id)
-            # Convert markdown to Telegram HTML
-            html_content = _markdown_to_telegram_html(msg.content)
-            await self._app.bot.send_message(
-                chat_id=chat_id,
-                text=html_content,
-                parse_mode="HTML"
-            )
        except ValueError:
            logger.error(f"Invalid chat_id: {msg.chat_id}")
+            return
+
+        # Send media files
+        for media_path in (msg.media or []):
+            try:
+                media_type = self._get_media_type(media_path)
+                sender = {
+                    "photo": self._app.bot.send_photo,
+                    "voice": self._app.bot.send_voice,
+                    "audio": self._app.bot.send_audio,
+                }.get(media_type, self._app.bot.send_document)
+                param = "photo" if media_type == "photo" else media_type if media_type in ("voice", "audio") else "document"
+                with open(media_path, 'rb') as f:
+                    await sender(chat_id=chat_id, **{param: f})
+            except Exception as e:
+                filename = media_path.rsplit("/", 1)[-1]
+                logger.error(f"Failed to send media {media_path}: {e}")
+                await self._app.bot.send_message(chat_id=chat_id, text=f"[Failed to send: {filename}]")
+
+        # Send text content
+        if msg.content and msg.content != "[empty message]":
+            for chunk in _split_message(msg.content):
+                try:
+                    html = _markdown_to_telegram_html(chunk)
+                    await self._app.bot.send_message(chat_id=chat_id, text=html, parse_mode="HTML")
                except Exception as e:
-            # Fallback to plain text if HTML parsing fails
                    logger.warning(f"HTML parse failed, falling back to plain text: {e}")
                    try:
-                await self._app.bot.send_message(
-                    chat_id=int(msg.chat_id),
-                    text=msg.content
-                )
+                        await self._app.bot.send_message(chat_id=chat_id, text=chunk)
                    except Exception as e2:
                        logger.error(f"Error sending Telegram message: {e2}")
    
@ -222,12 +266,18 @@ class TelegramChannel(BaseChannel):
            "Type /help to see available commands."
        )
    
+    @staticmethod
+    def _sender_id(user) -> str:
+        """Build sender_id with username for allowlist matching."""
+        sid = str(user.id)
+        return f"{sid}|{user.username}" if user.username else sid
+
    async def _forward_command(self, update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
        """Forward slash commands to the bus for unified handling in AgentLoop."""
        if not update.message or not update.effective_user:
            return
        await self._handle_message(
-            sender_id=str(update.effective_user.id),
+            sender_id=self._sender_id(update.effective_user),
            chat_id=str(update.message.chat_id),
            content=update.message.text,
        )
@ -240,11 +290,7 @@ class TelegramChannel(BaseChannel):
        message = update.message
        user = update.effective_user
        chat_id = message.chat_id
-        
-        # Use stable numeric ID, but keep username for allowlist compatibility
-        sender_id = str(user.id)
-        if user.username:
-            sender_id = f"{sender_id}|{user.username}"
+        sender_id = self._sender_id(user)
        
        # Store chat_id for replies
        self._chat_ids[sender_id] = chat_id
--- a/nanobot/cli/commands.py
+++ b/nanobot/cli/commands.py
@ -19,6 +19,7 @@ from prompt_toolkit.history import FileHistory
 from prompt_toolkit.patch_stdout import patch_stdout

 from nanobot import __version__, __logo__
+from nanobot.config.schema import Config

 app = typer.Typer(
    name="nanobot",
@ -278,21 +279,41 @@ This file stores important information that should persist across sessions.
    skills_dir.mkdir(exist_ok=True)


-def _make_provider(config):
-    """Create LiteLLMProvider from config. Exits if no API key found."""
+def _make_provider(config: Config):
+    """Create the appropriate LLM provider from config."""
    from nanobot.providers.litellm_provider import LiteLLMProvider
-    p = config.get_provider()
+    from nanobot.providers.openai_codex_provider import OpenAICodexProvider
+    from nanobot.providers.custom_provider import CustomProvider
+
    model = config.agents.defaults.model
-    if not (p and p.api_key) and not model.startswith("bedrock/"):
+    provider_name = config.get_provider_name(model)
+    p = config.get_provider(model)
+
+    # OpenAI Codex (OAuth)
+    if provider_name == "openai_codex" or model.startswith("openai-codex/"):
+        return OpenAICodexProvider(default_model=model)
+
+    # Custom: direct OpenAI-compatible endpoint, bypasses LiteLLM
+    if provider_name == "custom":
+        return CustomProvider(
+            api_key=p.api_key if p else "no-key",
+            api_base=config.get_api_base(model) or "http://localhost:8000/v1",
+            default_model=model,
+        )
+
+    from nanobot.providers.registry import find_by_name
+    spec = find_by_name(provider_name)
+    if not model.startswith("bedrock/") and not (p and p.api_key) and not (spec and spec.is_oauth):
        console.print("[red]Error: No API key configured.[/red]")
        console.print("Set one in ~/.nanobot/config.json under providers section")
        raise typer.Exit(1)
+
    return LiteLLMProvider(
        api_key=p.api_key if p else None,
-        api_base=config.get_api_base(),
+        api_base=config.get_api_base(model),
        default_model=model,
        extra_headers=p.extra_headers if p else None,
-        provider_name=config.get_provider_name(),
+        provider_name=provider_name,
    )


@ -346,6 +367,7 @@ def gateway(
        cron_service=cron,
        restrict_to_workspace=config.tools.restrict_to_workspace,
        session_manager=session_manager,
+        mcp_servers=config.tools.mcp_servers,
    )
    
    # Set cron callback (needs agent)
@ -403,6 +425,8 @@ def gateway(
            )
        except KeyboardInterrupt:
            console.print("\nShutting down...")
+        finally:
+            await agent.close_mcp()
            heartbeat.stop()
            cron.stop()
            agent.stop()
@ -426,9 +450,10 @@ def agent(
    logs: bool = typer.Option(False, "--logs/--no-logs", help="Show nanobot runtime logs during chat"),
 ):
    """Interact with the agent directly."""
-    from nanobot.config.loader import load_config
+    from nanobot.config.loader import load_config, get_data_dir
    from nanobot.bus.queue import MessageBus
    from nanobot.agent.loop import AgentLoop
+    from nanobot.cron.service import CronService
    from loguru import logger
    
    config = load_config()
@ -436,6 +461,10 @@ def agent(
    bus = MessageBus()
    provider = _make_provider(config)

+    # Create cron service for tool usage (no callback needed for CLI unless running)
+    cron_store_path = get_data_dir() / "cron" / "jobs.json"
+    cron = CronService(cron_store_path)
+
    if logs:
        logger.enable("nanobot")
    else:
@ -452,7 +481,9 @@ def agent(
        memory_window=config.agents.defaults.memory_window,
        brave_api_key=config.tools.web.search.api_key or None,
        exec_config=config.tools.exec,
+        cron_service=cron,
        restrict_to_workspace=config.tools.restrict_to_workspace,
+        mcp_servers=config.tools.mcp_servers,
    )
    
    # Show spinner when logs are off (no output to miss); skip when logs are on
@ -469,6 +500,7 @@ def agent(
            with _thinking_ctx():
                response = await agent_loop.process_direct(message, session_id)
            _print_agent_response(response, render_markdown=markdown)
+            await agent_loop.close_mcp()
        
        asyncio.run(run_once())
    else:
@ -484,6 +516,7 @@ def agent(
        signal.signal(signal.SIGINT, _exit_on_sigint)
        
        async def run_interactive():
+            try:
                while True:
                    try:
                        _flush_pending_tty_input()
@ -508,6 +541,8 @@ def agent(
                        _restore_terminal()
                        console.print("\nGoodbye!")
                        break
+            finally:
+                await agent_loop.close_mcp()
        
        asyncio.run(run_interactive())

@ -702,20 +737,26 @@ def cron_list(
    table.add_column("Next Run")
    
    import time
+    from datetime import datetime as _dt
+    from zoneinfo import ZoneInfo
    for job in jobs:
        # Format schedule
        if job.schedule.kind == "every":
            sched = f"every {(job.schedule.every_ms or 0) // 1000}s"
        elif job.schedule.kind == "cron":
-            sched = job.schedule.expr or ""
+            sched = f"{job.schedule.expr or ''} ({job.schedule.tz})" if job.schedule.tz else (job.schedule.expr or "")
        else:
            sched = "one-time"
        
        # Format next run
        next_run = ""
        if job.state.next_run_at_ms:
-            next_time = time.strftime("%Y-%m-%d %H:%M", time.localtime(job.state.next_run_at_ms / 1000))
-            next_run = next_time
+            ts = job.state.next_run_at_ms / 1000
+            try:
+                tz = ZoneInfo(job.schedule.tz) if job.schedule.tz else None
+                next_run = _dt.fromtimestamp(ts, tz).strftime("%Y-%m-%d %H:%M")
+            except Exception:
+                next_run = time.strftime("%Y-%m-%d %H:%M", time.localtime(ts))
        
        status = "[green]enabled[/green]" if job.enabled else "[dim]disabled[/dim]"
        
@ -730,6 +771,7 @@ def cron_add(
    message: str = typer.Option(..., "--message", "-m", help="Message for agent"),
    every: int = typer.Option(None, "--every", "-e", help="Run every N seconds"),
    cron_expr: str = typer.Option(None, "--cron", "-c", help="Cron expression (e.g. '0 9 * * *')"),
+    tz: str | None = typer.Option(None, "--tz", help="IANA timezone for cron (e.g. 'America/Vancouver')"),
    at: str = typer.Option(None, "--at", help="Run once at time (ISO format)"),
    deliver: bool = typer.Option(False, "--deliver", "-d", help="Deliver response to channel"),
    to: str = typer.Option(None, "--to", help="Recipient for delivery"),
@ -740,11 +782,15 @@ def cron_add(
    from nanobot.cron.service import CronService
    from nanobot.cron.types import CronSchedule
    
+    if tz and not cron_expr:
+        console.print("[red]Error: --tz can only be used with --cron[/red]")
+        raise typer.Exit(1)
+
    # Determine schedule type
    if every:
        schedule = CronSchedule(kind="every", every_ms=every * 1000)
    elif cron_expr:
-        schedule = CronSchedule(kind="cron", expr=cron_expr)
+        schedule = CronSchedule(kind="cron", expr=cron_expr, tz=tz)
    elif at:
        import datetime
        dt = datetime.datetime.fromisoformat(at)
@ -855,7 +901,9 @@ def status():
            p = getattr(config.providers, spec.name, None)
            if p is None:
                continue
-            if spec.is_local:
+            if spec.is_oauth:
+                console.print(f"{spec.label}: [green]✓ (OAuth)[/green]")
+            elif spec.is_local:
                # Local deployments show api_base instead of api_key
                if p.api_base:
                    console.print(f"{spec.label}: [green]✓ {p.api_base}[/green]")
@ -866,5 +914,88 @@ def status():
                console.print(f"{spec.label}: {'[green]✓[/green]' if has_key else '[dim]not set[/dim]'}")


+# ============================================================================
+# OAuth Login
+# ============================================================================
+
+provider_app = typer.Typer(help="Manage providers")
+app.add_typer(provider_app, name="provider")
+
+
+_LOGIN_HANDLERS: dict[str, callable] = {}
+
+
+def _register_login(name: str):
+    def decorator(fn):
+        _LOGIN_HANDLERS[name] = fn
+        return fn
+    return decorator
+
+
+@provider_app.command("login")
+def provider_login(
+    provider: str = typer.Argument(..., help="OAuth provider (e.g. 'openai-codex', 'github-copilot')"),
+):
+    """Authenticate with an OAuth provider."""
+    from nanobot.providers.registry import PROVIDERS
+
+    key = provider.replace("-", "_")
+    spec = next((s for s in PROVIDERS if s.name == key and s.is_oauth), None)
+    if not spec:
+        names = ", ".join(s.name.replace("_", "-") for s in PROVIDERS if s.is_oauth)
+        console.print(f"[red]Unknown OAuth provider: {provider}[/red]  Supported: {names}")
+        raise typer.Exit(1)
+
+    handler = _LOGIN_HANDLERS.get(spec.name)
+    if not handler:
+        console.print(f"[red]Login not implemented for {spec.label}[/red]")
+        raise typer.Exit(1)
+
+    console.print(f"{__logo__} OAuth Login - {spec.label}\n")
+    handler()
+
+
+@_register_login("openai_codex")
+def _login_openai_codex() -> None:
+    try:
+        from oauth_cli_kit import get_token, login_oauth_interactive
+        token = None
+        try:
+            token = get_token()
+        except Exception:
+            pass
+        if not (token and token.access):
+            console.print("[cyan]Starting interactive OAuth login...[/cyan]\n")
+            token = login_oauth_interactive(
+                print_fn=lambda s: console.print(s),
+                prompt_fn=lambda s: typer.prompt(s),
+            )
+        if not (token and token.access):
+            console.print("[red]✗ Authentication failed[/red]")
+            raise typer.Exit(1)
+        console.print(f"[green]✓ Authenticated with OpenAI Codex[/green]  [dim]{token.account_id}[/dim]")
+    except ImportError:
+        console.print("[red]oauth_cli_kit not installed. Run: pip install oauth-cli-kit[/red]")
+        raise typer.Exit(1)
+
+
+@_register_login("github_copilot")
+def _login_github_copilot() -> None:
+    import asyncio
+
+    console.print("[cyan]Starting GitHub Copilot device flow...[/cyan]\n")
+
+    async def _trigger():
+        from litellm import acompletion
+        await acompletion(model="github_copilot/gpt-4o", messages=[{"role": "user", "content": "hi"}], max_tokens=1)
+
+    try:
+        asyncio.run(_trigger())
+        console.print("[green]✓ Authenticated with GitHub Copilot[/green]")
+    except Exception as e:
+        console.print(f"[red]Authentication error: {e}[/red]")
+        raise typer.Exit(1)
+
+
 if __name__ == "__main__":
    app()
--- a/nanobot/config/loader.py
+++ b/nanobot/config/loader.py
@ -2,7 +2,6 @@

 import json
 from pathlib import Path
-from typing import Any

 from nanobot.config.schema import Config

@ -35,7 +34,7 @@ def load_config(config_path: Path | None = None) -> Config:
            with open(path) as f:
                data = json.load(f)
            data = _migrate_config(data)
-            return Config.model_validate(convert_keys(data))
+            return Config.model_validate(data)
        except (json.JSONDecodeError, ValueError) as e:
            print(f"Warning: Failed to load config from {path}: {e}")
            print("Using default configuration.")
@ -54,9 +53,7 @@ def save_config(config: Config, config_path: Path | None = None) -> None:
    path = config_path or get_config_path()
    path.parent.mkdir(parents=True, exist_ok=True)

-    # Convert to camelCase format
-    data = config.model_dump()
-    data = convert_to_camel(data)
+    data = config.model_dump(by_alias=True)

    with open(path, "w") as f:
        json.dump(data, f, indent=2)
@ -70,37 +67,3 @@ def _migrate_config(data: dict) -> dict:
    if "restrictToWorkspace" in exec_cfg and "restrictToWorkspace" not in tools:
        tools["restrictToWorkspace"] = exec_cfg.pop("restrictToWorkspace")
    return data
-
-
-def convert_keys(data: Any) -> Any:
-    """Convert camelCase keys to snake_case for Pydantic."""
-    if isinstance(data, dict):
-        return {camel_to_snake(k): convert_keys(v) for k, v in data.items()}
-    if isinstance(data, list):
-        return [convert_keys(item) for item in data]
-    return data
-
-
-def convert_to_camel(data: Any) -> Any:
-    """Convert snake_case keys to camelCase."""
-    if isinstance(data, dict):
-        return {snake_to_camel(k): convert_to_camel(v) for k, v in data.items()}
-    if isinstance(data, list):
-        return [convert_to_camel(item) for item in data]
-    return data
-
-
-def camel_to_snake(name: str) -> str:
-    """Convert camelCase to snake_case."""
-    result = []
-    for i, char in enumerate(name):
-        if char.isupper() and i > 0:
-            result.append("_")
-        result.append(char.lower())
-    return "".join(result)
-
-
-def snake_to_camel(name: str) -> str:
-    """Convert snake_case to camelCase."""
-    components = name.split("_")
-    return components[0] + "".join(x.title() for x in components[1:])
--- a/nanobot/config/schema.py
+++ b/nanobot/config/schema.py
@ -2,27 +2,37 @@

 from pathlib import Path
 from pydantic import BaseModel, Field, ConfigDict
+from pydantic.alias_generators import to_camel
 from pydantic_settings import BaseSettings


-class WhatsAppConfig(BaseModel):
+class Base(BaseModel):
+    """Base model that accepts both camelCase and snake_case keys."""
+
+    model_config = ConfigDict(alias_generator=to_camel, populate_by_name=True)
+
+
+class WhatsAppConfig(Base):
    """WhatsApp channel configuration."""
+
    enabled: bool = False
    bridge_url: str = "ws://localhost:3001"
    bridge_token: str = ""  # Shared token for bridge auth (optional, recommended)
    allow_from: list[str] = Field(default_factory=list)  # Allowed phone numbers


-class TelegramConfig(BaseModel):
+class TelegramConfig(Base):
    """Telegram channel configuration."""
+
    enabled: bool = False
    token: str = ""  # Bot token from @BotFather
    allow_from: list[str] = Field(default_factory=list)  # Allowed user IDs or usernames
    proxy: str | None = None  # HTTP/SOCKS5 proxy URL, e.g. "http://127.0.0.1:7890" or "socks5://127.0.0.1:1080"


-class FeishuConfig(BaseModel):
+class FeishuConfig(Base):
    """Feishu/Lark channel configuration using WebSocket long connection."""
+
    enabled: bool = False
    app_id: str = ""  # App ID from Feishu Open Platform
    app_secret: str = ""  # App Secret from Feishu Open Platform
@ -31,24 +41,28 @@ class FeishuConfig(BaseModel):
    allow_from: list[str] = Field(default_factory=list)  # Allowed user open_ids


-class DingTalkConfig(BaseModel):
+class DingTalkConfig(Base):
    """DingTalk channel configuration using Stream mode."""
+
    enabled: bool = False
    client_id: str = ""  # AppKey
    client_secret: str = ""  # AppSecret
    allow_from: list[str] = Field(default_factory=list)  # Allowed staff_ids


-class DiscordConfig(BaseModel):
+class DiscordConfig(Base):
    """Discord channel configuration."""
+
    enabled: bool = False
    token: str = ""  # Bot token from Discord Developer Portal
    allow_from: list[str] = Field(default_factory=list)  # Allowed user IDs
    gateway_url: str = "wss://gateway.discord.gg/?v=10&encoding=json"
    intents: int = 37377  # GUILDS + GUILD_MESSAGES + DIRECT_MESSAGES + MESSAGE_CONTENT

-class EmailConfig(BaseModel):
+
+class EmailConfig(Base):
    """Email channel configuration (IMAP inbound + SMTP outbound)."""
+
    enabled: bool = False
    consent_granted: bool = False  # Explicit owner permission to access mailbox data

@ -78,18 +92,21 @@ class EmailConfig(BaseModel):
    allow_from: list[str] = Field(default_factory=list)  # Allowed sender email addresses


-class MochatMentionConfig(BaseModel):
+class MochatMentionConfig(Base):
    """Mochat mention behavior configuration."""
+
    require_in_groups: bool = False


-class MochatGroupRule(BaseModel):
+class MochatGroupRule(Base):
    """Mochat per-group mention requirement."""
+
    require_mention: bool = False


-class MochatConfig(BaseModel):
+class MochatConfig(Base):
    """Mochat channel configuration."""
+
    enabled: bool = False
    base_url: str = "https://mochat.io"
    socket_url: str = ""
@ -114,36 +131,42 @@ class MochatConfig(BaseModel):
    reply_delay_ms: int = 120000


-class SlackDMConfig(BaseModel):
+class SlackDMConfig(Base):
    """Slack DM policy configuration."""
+
    enabled: bool = True
    policy: str = "open"  # "open" or "allowlist"
    allow_from: list[str] = Field(default_factory=list)  # Allowed Slack user IDs


-class SlackConfig(BaseModel):
+class SlackConfig(Base):
    """Slack channel configuration."""
+
    enabled: bool = False
    mode: str = "socket"  # "socket" supported
    webhook_path: str = "/slack/events"
    bot_token: str = ""  # xoxb-...
    app_token: str = ""  # xapp-...
    user_token_read_only: bool = True
+    reply_in_thread: bool = True
+    react_emoji: str = "eyes"
    group_policy: str = "mention"  # "mention", "open", "allowlist"
    group_allow_from: list[str] = Field(default_factory=list)  # Allowed channel IDs if allowlist
    dm: SlackDMConfig = Field(default_factory=SlackDMConfig)


-class QQConfig(BaseModel):
+class QQConfig(Base):
    """QQ channel configuration using botpy SDK."""
+
    enabled: bool = False
    app_id: str = ""  # 机器人 ID (AppID) from q.qq.com
    secret: str = ""  # 机器人密钥 (AppSecret) from q.qq.com
    allow_from: list[str] = Field(default_factory=list)  # Allowed user openids (empty = public access)


-class ChannelsConfig(BaseModel):
+class ChannelsConfig(Base):
    """Configuration for chat channels."""
+
    whatsapp: WhatsAppConfig = Field(default_factory=WhatsAppConfig)
    telegram: TelegramConfig = Field(default_factory=TelegramConfig)
    discord: DiscordConfig = Field(default_factory=DiscordConfig)
@ -155,8 +178,9 @@ class ChannelsConfig(BaseModel):
    qq: QQConfig = Field(default_factory=QQConfig)


-class AgentDefaults(BaseModel):
+class AgentDefaults(Base):
    """Default agent configuration."""
+
    workspace: str = "~/.nanobot/workspace"
    model: str = "anthropic/claude-opus-4-5"
    max_tokens: int = 8192
@ -165,20 +189,23 @@ class AgentDefaults(BaseModel):
    memory_window: int = 50


-class AgentsConfig(BaseModel):
+class AgentsConfig(Base):
    """Agent configuration."""
+
    defaults: AgentDefaults = Field(default_factory=AgentDefaults)


-class ProviderConfig(BaseModel):
+class ProviderConfig(Base):
    """LLM provider configuration."""
+
    api_key: str = ""
    api_base: str | None = None
    extra_headers: dict[str, str] | None = None  # Custom headers (e.g. APP-Code for AiHubMix)


-class ProvidersConfig(BaseModel):
+class ProvidersConfig(Base):
    """Configuration for LLM providers."""
+
    custom: ProviderConfig = Field(default_factory=ProviderConfig)  # Any OpenAI-compatible endpoint
    anthropic: ProviderConfig = Field(default_factory=ProviderConfig)
    openai: ProviderConfig = Field(default_factory=ProviderConfig)
@ -192,39 +219,58 @@ class ProvidersConfig(BaseModel):
    moonshot: ProviderConfig = Field(default_factory=ProviderConfig)
    minimax: ProviderConfig = Field(default_factory=ProviderConfig)
    aihubmix: ProviderConfig = Field(default_factory=ProviderConfig)  # AiHubMix API gateway
+    siliconflow: ProviderConfig = Field(default_factory=ProviderConfig)  # SiliconFlow (硅基流动) API gateway
+    openai_codex: ProviderConfig = Field(default_factory=ProviderConfig)  # OpenAI Codex (OAuth)
+    github_copilot: ProviderConfig = Field(default_factory=ProviderConfig)  # Github Copilot (OAuth)


-class GatewayConfig(BaseModel):
+class GatewayConfig(Base):
    """Gateway/server configuration."""
+
    host: str = "0.0.0.0"
    port: int = 18790


-class WebSearchConfig(BaseModel):
+class WebSearchConfig(Base):
    """Web search tool configuration."""
+
    api_key: str = ""  # Brave Search API key
    max_results: int = 5


-class WebToolsConfig(BaseModel):
+class WebToolsConfig(Base):
    """Web tools configuration."""
+
    search: WebSearchConfig = Field(default_factory=WebSearchConfig)


-class ExecToolConfig(BaseModel):
+class ExecToolConfig(Base):
    """Shell exec tool configuration."""
+
    timeout: int = 60


-class ToolsConfig(BaseModel):
+class MCPServerConfig(Base):
+    """MCP server connection configuration (stdio or HTTP)."""
+
+    command: str = ""  # Stdio: command to run (e.g. "npx")
+    args: list[str] = Field(default_factory=list)  # Stdio: command arguments
+    env: dict[str, str] = Field(default_factory=dict)  # Stdio: extra env vars
+    url: str = ""  # HTTP: streamable HTTP endpoint URL
+
+
+class ToolsConfig(Base):
    """Tools configuration."""
+
    web: WebToolsConfig = Field(default_factory=WebToolsConfig)
    exec: ExecToolConfig = Field(default_factory=ExecToolConfig)
    restrict_to_workspace: bool = False  # If true, restrict all tool access to workspace directory
+    mcp_servers: dict[str, MCPServerConfig] = Field(default_factory=dict)


 class Config(BaseSettings):
    """Root configuration for nanobot."""
+
    agents: AgentsConfig = Field(default_factory=AgentsConfig)
    channels: ChannelsConfig = Field(default_factory=ChannelsConfig)
    providers: ProvidersConfig = Field(default_factory=ProvidersConfig)
@ -239,16 +285,21 @@ class Config(BaseSettings):
    def _match_provider(self, model: str | None = None) -> tuple["ProviderConfig | None", str | None]:
        """Match provider config and its registry name. Returns (config, spec_name)."""
        from nanobot.providers.registry import PROVIDERS
+
        model_lower = (model or self.agents.defaults.model).lower()

        # Match by keyword (order follows PROVIDERS registry)
        for spec in PROVIDERS:
            p = getattr(self.providers, spec.name, None)
-            if p and any(kw in model_lower for kw in spec.keywords) and p.api_key:
+            if p and any(kw in model_lower for kw in spec.keywords):
+                if spec.is_oauth or p.api_key:
                    return p, spec.name

        # Fallback: gateways first, then others (follows registry order)
+        # OAuth providers are NOT valid fallbacks — they require explicit model selection
        for spec in PROVIDERS:
+            if spec.is_oauth:
+                continue
            p = getattr(self.providers, spec.name, None)
            if p and p.api_key:
                return p, spec.name
@ -272,6 +323,7 @@ class Config(BaseSettings):
    def get_api_base(self, model: str | None = None) -> str | None:
        """Get API base URL for the given model. Applies default URLs for known gateways."""
        from nanobot.providers.registry import find_by_name
+
        p, name = self._match_provider(model)
        if p and p.api_base:
            return p.api_base
@ -284,7 +336,4 @@ class Config(BaseSettings):
                return spec.default_api_base
        return None

-    model_config = ConfigDict(
-        env_prefix="NANOBOT_",
-        env_nested_delimiter="__"
-    )
+    model_config = ConfigDict(env_prefix="NANOBOT_", env_nested_delimiter="__")
--- a/nanobot/cron/service.py
+++ b/nanobot/cron/service.py
@ -4,6 +4,7 @@ import asyncio
 import json
 import time
 import uuid
+from datetime import datetime
 from pathlib import Path
 from typing import Any, Callable, Coroutine

@ -30,9 +31,14 @@ def _compute_next_run(schedule: CronSchedule, now_ms: int) -> int | None:
    if schedule.kind == "cron" and schedule.expr:
        try:
            from croniter import croniter
-            cron = croniter(schedule.expr, time.time())
-            next_time = cron.get_next()
-            return int(next_time * 1000)
+            from zoneinfo import ZoneInfo
+            # Use caller-provided reference time for deterministic scheduling
+            base_time = now_ms / 1000
+            tz = ZoneInfo(schedule.tz) if schedule.tz else datetime.now().astimezone().tzinfo
+            base_dt = datetime.fromtimestamp(base_time, tz=tz)
+            cron = croniter(schedule.expr, base_dt)
+            next_dt = cron.get_next(datetime)
+            return int(next_dt.timestamp() * 1000)
        except Exception:
            return None
    
--- a/nanobot/providers/init.py
+++ b/nanobot/providers/init.py
@ -2,5 +2,6 @@

 from nanobot.providers.base import LLMProvider, LLMResponse
 from nanobot.providers.litellm_provider import LiteLLMProvider
+from nanobot.providers.openai_codex_provider import OpenAICodexProvider

-__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider"]
+__all__ = ["LLMProvider", "LLMResponse", "LiteLLMProvider", "OpenAICodexProvider"]
--- a/nanobot/providers/custom_provider.py
+++ b/nanobot/providers/custom_provider.py
@ -0,0 +1,47 @@
+"""Direct OpenAI-compatible provider — bypasses LiteLLM."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import json_repair
+from openai import AsyncOpenAI
+
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
+
+
+class CustomProvider(LLMProvider):
+
+    def __init__(self, api_key: str = "no-key", api_base: str = "http://localhost:8000/v1", default_model: str = "default"):
+        super().__init__(api_key, api_base)
+        self.default_model = default_model
+        self._client = AsyncOpenAI(api_key=api_key, base_url=api_base)
+
+    async def chat(self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
+                   model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7) -> LLMResponse:
+        kwargs: dict[str, Any] = {"model": model or self.default_model, "messages": messages,
+                                  "max_tokens": max(1, max_tokens), "temperature": temperature}
+        if tools:
+            kwargs.update(tools=tools, tool_choice="auto")
+        try:
+            return self._parse(await self._client.chat.completions.create(**kwargs))
+        except Exception as e:
+            return LLMResponse(content=f"Error: {e}", finish_reason="error")
+
+    def _parse(self, response: Any) -> LLMResponse:
+        choice = response.choices[0]
+        msg = choice.message
+        tool_calls = [
+            ToolCallRequest(id=tc.id, name=tc.function.name,
+                            arguments=json_repair.loads(tc.function.arguments) if isinstance(tc.function.arguments, str) else tc.function.arguments)
+            for tc in (msg.tool_calls or [])
+        ]
+        u = response.usage
+        return LLMResponse(
+            content=msg.content, tool_calls=tool_calls, finish_reason=choice.finish_reason or "stop",
+            usage={"prompt_tokens": u.prompt_tokens, "completion_tokens": u.completion_tokens, "total_tokens": u.total_tokens} if u else {},
+            reasoning_content=getattr(msg, "reasoning_content", None),
+        )
+
+    def get_default_model(self) -> str:
+        return self.default_model
--- a/nanobot/providers/litellm_provider.py
+++ b/nanobot/providers/litellm_provider.py
@ -1,6 +1,7 @@
 """LiteLLM provider implementation for multi-provider support."""

 import json
+import json_repair
 import os
 from typing import Any

@ -54,6 +55,9 @@ class LiteLLMProvider(LLMProvider):
        spec = self._gateway or find_by_model(model)
        if not spec:
            return
+        if not spec.env_key:
+            # OAuth/provider-only specs (for example: openai_codex)
+            return

        # Gateway/local overrides existing env; standard provider doesn't
        if self._gateway:
@ -173,10 +177,7 @@ class LiteLLMProvider(LLMProvider):
                # Parse arguments from JSON string if needed
                args = tc.function.arguments
                if isinstance(args, str):
-                    try:
-                        args = json.loads(args)
-                    except json.JSONDecodeError:
-                        args = {"raw": args}
+                    args = json_repair.loads(args)
                
                tool_calls.append(ToolCallRequest(
                    id=tc.id,
--- a/nanobot/providers/openai_codex_provider.py
+++ b/nanobot/providers/openai_codex_provider.py
@ -0,0 +1,312 @@
+"""OpenAI Codex Responses Provider."""
+
+from __future__ import annotations
+
+import asyncio
+import hashlib
+import json
+from typing import Any, AsyncGenerator
+
+import httpx
+from loguru import logger
+
+from oauth_cli_kit import get_token as get_codex_token
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
+
+DEFAULT_CODEX_URL = "https://chatgpt.com/backend-api/codex/responses"
+DEFAULT_ORIGINATOR = "nanobot"
+
+
+class OpenAICodexProvider(LLMProvider):
+    """Use Codex OAuth to call the Responses API."""
+
+    def __init__(self, default_model: str = "openai-codex/gpt-5.1-codex"):
+        super().__init__(api_key=None, api_base=None)
+        self.default_model = default_model
+
+    async def chat(
+        self,
+        messages: list[dict[str, Any]],
+        tools: list[dict[str, Any]] | None = None,
+        model: str | None = None,
+        max_tokens: int = 4096,
+        temperature: float = 0.7,
+    ) -> LLMResponse:
+        model = model or self.default_model
+        system_prompt, input_items = _convert_messages(messages)
+
+        token = await asyncio.to_thread(get_codex_token)
+        headers = _build_headers(token.account_id, token.access)
+
+        body: dict[str, Any] = {
+            "model": _strip_model_prefix(model),
+            "store": False,
+            "stream": True,
+            "instructions": system_prompt,
+            "input": input_items,
+            "text": {"verbosity": "medium"},
+            "include": ["reasoning.encrypted_content"],
+            "prompt_cache_key": _prompt_cache_key(messages),
+            "tool_choice": "auto",
+            "parallel_tool_calls": True,
+        }
+
+        if tools:
+            body["tools"] = _convert_tools(tools)
+
+        url = DEFAULT_CODEX_URL
+
+        try:
+            try:
+                content, tool_calls, finish_reason = await _request_codex(url, headers, body, verify=True)
+            except Exception as e:
+                if "CERTIFICATE_VERIFY_FAILED" not in str(e):
+                    raise
+                logger.warning("SSL certificate verification failed for Codex API; retrying with verify=False")
+                content, tool_calls, finish_reason = await _request_codex(url, headers, body, verify=False)
+            return LLMResponse(
+                content=content,
+                tool_calls=tool_calls,
+                finish_reason=finish_reason,
+            )
+        except Exception as e:
+            return LLMResponse(
+                content=f"Error calling Codex: {str(e)}",
+                finish_reason="error",
+            )
+
+    def get_default_model(self) -> str:
+        return self.default_model
+
+
+def _strip_model_prefix(model: str) -> str:
+    if model.startswith("openai-codex/"):
+        return model.split("/", 1)[1]
+    return model
+
+
+def _build_headers(account_id: str, token: str) -> dict[str, str]:
+    return {
+        "Authorization": f"Bearer {token}",
+        "chatgpt-account-id": account_id,
+        "OpenAI-Beta": "responses=experimental",
+        "originator": DEFAULT_ORIGINATOR,
+        "User-Agent": "nanobot (python)",
+        "accept": "text/event-stream",
+        "content-type": "application/json",
+    }
+
+
+async def _request_codex(
+    url: str,
+    headers: dict[str, str],
+    body: dict[str, Any],
+    verify: bool,
+) -> tuple[str, list[ToolCallRequest], str]:
+    async with httpx.AsyncClient(timeout=60.0, verify=verify) as client:
+        async with client.stream("POST", url, headers=headers, json=body) as response:
+            if response.status_code != 200:
+                text = await response.aread()
+                raise RuntimeError(_friendly_error(response.status_code, text.decode("utf-8", "ignore")))
+            return await _consume_sse(response)
+
+
+def _convert_tools(tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    """Convert OpenAI function-calling schema to Codex flat format."""
+    converted: list[dict[str, Any]] = []
+    for tool in tools:
+        fn = (tool.get("function") or {}) if tool.get("type") == "function" else tool
+        name = fn.get("name")
+        if not name:
+            continue
+        params = fn.get("parameters") or {}
+        converted.append({
+            "type": "function",
+            "name": name,
+            "description": fn.get("description") or "",
+            "parameters": params if isinstance(params, dict) else {},
+        })
+    return converted
+
+
+def _convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str, Any]]]:
+    system_prompt = ""
+    input_items: list[dict[str, Any]] = []
+
+    for idx, msg in enumerate(messages):
+        role = msg.get("role")
+        content = msg.get("content")
+
+        if role == "system":
+            system_prompt = content if isinstance(content, str) else ""
+            continue
+
+        if role == "user":
+            input_items.append(_convert_user_message(content))
+            continue
+
+        if role == "assistant":
+            # Handle text first.
+            if isinstance(content, str) and content:
+                input_items.append(
+                    {
+                        "type": "message",
+                        "role": "assistant",
+                        "content": [{"type": "output_text", "text": content}],
+                        "status": "completed",
+                        "id": f"msg_{idx}",
+                    }
+                )
+            # Then handle tool calls.
+            for tool_call in msg.get("tool_calls", []) or []:
+                fn = tool_call.get("function") or {}
+                call_id, item_id = _split_tool_call_id(tool_call.get("id"))
+                call_id = call_id or f"call_{idx}"
+                item_id = item_id or f"fc_{idx}"
+                input_items.append(
+                    {
+                        "type": "function_call",
+                        "id": item_id,
+                        "call_id": call_id,
+                        "name": fn.get("name"),
+                        "arguments": fn.get("arguments") or "{}",
+                    }
+                )
+            continue
+
+        if role == "tool":
+            call_id, _ = _split_tool_call_id(msg.get("tool_call_id"))
+            output_text = content if isinstance(content, str) else json.dumps(content)
+            input_items.append(
+                {
+                    "type": "function_call_output",
+                    "call_id": call_id,
+                    "output": output_text,
+                }
+            )
+            continue
+
+    return system_prompt, input_items
+
+
+def _convert_user_message(content: Any) -> dict[str, Any]:
+    if isinstance(content, str):
+        return {"role": "user", "content": [{"type": "input_text", "text": content}]}
+    if isinstance(content, list):
+        converted: list[dict[str, Any]] = []
+        for item in content:
+            if not isinstance(item, dict):
+                continue
+            if item.get("type") == "text":
+                converted.append({"type": "input_text", "text": item.get("text", "")})
+            elif item.get("type") == "image_url":
+                url = (item.get("image_url") or {}).get("url")
+                if url:
+                    converted.append({"type": "input_image", "image_url": url, "detail": "auto"})
+        if converted:
+            return {"role": "user", "content": converted}
+    return {"role": "user", "content": [{"type": "input_text", "text": ""}]}
+
+
+def _split_tool_call_id(tool_call_id: Any) -> tuple[str, str | None]:
+    if isinstance(tool_call_id, str) and tool_call_id:
+        if "|" in tool_call_id:
+            call_id, item_id = tool_call_id.split("|", 1)
+            return call_id, item_id or None
+        return tool_call_id, None
+    return "call_0", None
+
+
+def _prompt_cache_key(messages: list[dict[str, Any]]) -> str:
+    raw = json.dumps(messages, ensure_ascii=True, sort_keys=True)
+    return hashlib.sha256(raw.encode("utf-8")).hexdigest()
+
+
+async def _iter_sse(response: httpx.Response) -> AsyncGenerator[dict[str, Any], None]:
+    buffer: list[str] = []
+    async for line in response.aiter_lines():
+        if line == "":
+            if buffer:
+                data_lines = [l[5:].strip() for l in buffer if l.startswith("data:")]
+                buffer = []
+                if not data_lines:
+                    continue
+                data = "\n".join(data_lines).strip()
+                if not data or data == "[DONE]":
+                    continue
+                try:
+                    yield json.loads(data)
+                except Exception:
+                    continue
+            continue
+        buffer.append(line)
+
+
+async def _consume_sse(response: httpx.Response) -> tuple[str, list[ToolCallRequest], str]:
+    content = ""
+    tool_calls: list[ToolCallRequest] = []
+    tool_call_buffers: dict[str, dict[str, Any]] = {}
+    finish_reason = "stop"
+
+    async for event in _iter_sse(response):
+        event_type = event.get("type")
+        if event_type == "response.output_item.added":
+            item = event.get("item") or {}
+            if item.get("type") == "function_call":
+                call_id = item.get("call_id")
+                if not call_id:
+                    continue
+                tool_call_buffers[call_id] = {
+                    "id": item.get("id") or "fc_0",
+                    "name": item.get("name"),
+                    "arguments": item.get("arguments") or "",
+                }
+        elif event_type == "response.output_text.delta":
+            content += event.get("delta") or ""
+        elif event_type == "response.function_call_arguments.delta":
+            call_id = event.get("call_id")
+            if call_id and call_id in tool_call_buffers:
+                tool_call_buffers[call_id]["arguments"] += event.get("delta") or ""
+        elif event_type == "response.function_call_arguments.done":
+            call_id = event.get("call_id")
+            if call_id and call_id in tool_call_buffers:
+                tool_call_buffers[call_id]["arguments"] = event.get("arguments") or ""
+        elif event_type == "response.output_item.done":
+            item = event.get("item") or {}
+            if item.get("type") == "function_call":
+                call_id = item.get("call_id")
+                if not call_id:
+                    continue
+                buf = tool_call_buffers.get(call_id) or {}
+                args_raw = buf.get("arguments") or item.get("arguments") or "{}"
+                try:
+                    args = json.loads(args_raw)
+                except Exception:
+                    args = {"raw": args_raw}
+                tool_calls.append(
+                    ToolCallRequest(
+                        id=f"{call_id}|{buf.get('id') or item.get('id') or 'fc_0'}",
+                        name=buf.get("name") or item.get("name"),
+                        arguments=args,
+                    )
+                )
+        elif event_type == "response.completed":
+            status = (event.get("response") or {}).get("status")
+            finish_reason = _map_finish_reason(status)
+        elif event_type in {"error", "response.failed"}:
+            raise RuntimeError("Codex response failed")
+
+    return content, tool_calls, finish_reason
+
+
+_FINISH_REASON_MAP = {"completed": "stop", "incomplete": "length", "failed": "error", "cancelled": "error"}
+
+
+def _map_finish_reason(status: str | None) -> str:
+    return _FINISH_REASON_MAP.get(status or "completed", "stop")
+
+
+def _friendly_error(status_code: int, raw: str) -> str:
+    if status_code == 429:
+        return "ChatGPT usage quota exceeded or rate limit triggered. Please try again later."
+    return f"HTTP {status_code}: {raw}"
--- a/nanobot/providers/registry.py
+++ b/nanobot/providers/registry.py
@ -51,6 +51,12 @@ class ProviderSpec:
    # per-model param overrides, e.g. (("kimi-k2.5", {"temperature": 1.0}),)
    model_overrides: tuple[tuple[str, dict[str, Any]], ...] = ()

+    # OAuth-based providers (e.g., OpenAI Codex) don't use API keys
+    is_oauth: bool = False                   # if True, uses OAuth flow instead of API key
+
+    # Direct providers bypass LiteLLM entirely (e.g., CustomProvider)
+    is_direct: bool = False
+
    @property
    def label(self) -> str:
        return self.display_name or self.name.title()
@ -62,18 +68,14 @@ class ProviderSpec:

 PROVIDERS: tuple[ProviderSpec, ...] = (

-    # === Custom (user-provided OpenAI-compatible endpoint) =================
-    # No auto-detection — only activates when user explicitly configures "custom".
-
+    # === Custom (direct OpenAI-compatible endpoint, bypasses LiteLLM) ======
    ProviderSpec(
        name="custom",
        keywords=(),
-        env_key="OPENAI_API_KEY",
+        env_key="",
        display_name="Custom",
-        litellm_prefix="openai",
-        skip_prefixes=("openai/",),
-        is_gateway=True,
-        strip_model_prefix=True,
+        litellm_prefix="",
+        is_direct=True,
    ),

    # === Gateways (detected by api_key / api_base, not model name) =========
@ -117,6 +119,24 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
        model_overrides=(),
    ),

+    # SiliconFlow (硅基流动): OpenAI-compatible gateway, model names keep org prefix
+    ProviderSpec(
+        name="siliconflow",
+        keywords=("siliconflow",),
+        env_key="OPENAI_API_KEY",
+        display_name="SiliconFlow",
+        litellm_prefix="openai",
+        skip_prefixes=(),
+        env_extras=(),
+        is_gateway=True,
+        is_local=False,
+        detect_by_key_prefix="",
+        detect_by_base_keyword="siliconflow",
+        default_api_base="https://api.siliconflow.cn/v1",
+        strip_model_prefix=False,
+        model_overrides=(),
+    ),
+
    # === Standard providers (matched by model-name keywords) ===============

    # Anthropic: LiteLLM recognizes "claude-*" natively, no prefix needed.
@ -155,6 +175,44 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
        model_overrides=(),
    ),

+    # OpenAI Codex: uses OAuth, not API key.
+    ProviderSpec(
+        name="openai_codex",
+        keywords=("openai-codex", "codex"),
+        env_key="",                         # OAuth-based, no API key
+        display_name="OpenAI Codex",
+        litellm_prefix="",                  # Not routed through LiteLLM
+        skip_prefixes=(),
+        env_extras=(),
+        is_gateway=False,
+        is_local=False,
+        detect_by_key_prefix="",
+        detect_by_base_keyword="codex",
+        default_api_base="https://chatgpt.com/backend-api",
+        strip_model_prefix=False,
+        model_overrides=(),
+        is_oauth=True,                      # OAuth-based authentication
+    ),
+
+    # Github Copilot: uses OAuth, not API key.
+    ProviderSpec(
+        name="github_copilot",
+        keywords=("github_copilot", "copilot"),
+        env_key="",                         # OAuth-based, no API key
+        display_name="Github Copilot",
+        litellm_prefix="github_copilot",   # github_copilot/model → github_copilot/model
+        skip_prefixes=("github_copilot/",),
+        env_extras=(),
+        is_gateway=False,
+        is_local=False,
+        detect_by_key_prefix="",
+        detect_by_base_keyword="",
+        default_api_base="",
+        strip_model_prefix=False,
+        model_overrides=(),
+        is_oauth=True,                      # OAuth-based authentication
+    ),
+
    # DeepSeek: needs "deepseek/" prefix for LiteLLM routing.
    ProviderSpec(
        name="deepseek",
--- a/nanobot/skills/README.md
+++ b/nanobot/skills/README.md
@ -21,4 +21,5 @@ The skill format and metadata structure follow OpenClaw's conventions to maintai
 | `weather` | Get weather info using wttr.in and Open-Meteo |
 | `summarize` | Summarize URLs, files, and YouTube videos |
 | `tmux` | Remote-control tmux sessions |
+| `clawhub` | Search and install skills from ClawHub registry |
 | `skill-creator` | Create new skills |
--- a/nanobot/skills/clawhub/SKILL.md
+++ b/nanobot/skills/clawhub/SKILL.md
@ -0,0 +1,53 @@
+---
+name: clawhub
+description: Search and install agent skills from ClawHub, the public skill registry.
+homepage: https://clawhub.ai
+metadata: {"nanobot":{"emoji":"🦞"}}
+---
+
+# ClawHub
+
+Public skill registry for AI agents. Search by natural language (vector search).
+
+## When to use
+
+Use this skill when the user asks any of:
+- "find a skill for …"
+- "search for skills"
+- "install a skill"
+- "what skills are available?"
+- "update my skills"
+
+## Search
+
+```bash
+npx --yes clawhub@latest search "web scraping" --limit 5
+```
+
+## Install
+
+```bash
+npx --yes clawhub@latest install <slug> --workdir ~/.nanobot/workspace
+```
+
+Replace `<slug>` with the skill name from search results. This places the skill into `~/.nanobot/workspace/skills/`, where nanobot loads workspace skills from. Always include `--workdir`.
+
+## Update
+
+```bash
+npx --yes clawhub@latest update --all --workdir ~/.nanobot/workspace
+```
+
+## List installed
+
+```bash
+npx --yes clawhub@latest list --workdir ~/.nanobot/workspace
+```
+
+## Notes
+
+- Requires Node.js (`npx` comes with it).
+- No API key needed for search and install.
+- Login (`npx --yes clawhub@latest login`) is only required for publishing.
+- `--workdir ~/.nanobot/workspace` is critical — without it, skills install to the current directory instead of the nanobot workspace.
+- After install, remind the user to start a new session to load the skill.
--- a/nanobot/skills/cron/SKILL.md
+++ b/nanobot/skills/cron/SKILL.md
@ -30,6 +30,11 @@ One-time scheduled task (compute ISO datetime from current time):
 cron(action="add", message="Remind me about the meeting", at="<ISO datetime>")
 ```

+Timezone-aware cron:
+```
+cron(action="add", message="Morning standup", cron_expr="0 9 * * 1-5", tz="America/Vancouver")
+```
+
 List/remove:
 ```
 cron(action="list")
@ -44,4 +49,9 @@ cron(action="remove", job_id="abc123")
 | every hour | every_seconds: 3600 |
 | every day at 8am | cron_expr: "0 8 * * *" |
 | weekdays at 5pm | cron_expr: "0 17 * * 1-5" |
+| 9am Vancouver time daily | cron_expr: "0 9 * * *", tz: "America/Vancouver" |
 | at a specific time | at: ISO datetime string (compute from current time) |
+
+## Timezone
+
+Use `tz` with `cron_expr` to schedule in a specific IANA timezone. Without `tz`, the server's local timezone is used.
--- a/pyproject.toml
+++ b/pyproject.toml
@ -23,7 +23,8 @@ dependencies = [
    "pydantic-settings>=2.0.0",
    "websockets>=12.0",
    "websocket-client>=1.6.0",
-    "httpx[socks]>=0.25.0",
+    "httpx>=0.25.0",
+    "oauth-cli-kit>=0.1.1",
    "loguru>=0.7.0",
    "readability-lxml>=0.8.0",
    "rich>=13.0.0",
@ -35,9 +36,12 @@ dependencies = [
    "python-socketio>=5.11.0",
    "msgpack>=1.0.8",
    "slack-sdk>=3.26.0",
+    "slackify-markdown>=0.2.0",
    "qq-botpy>=1.0.0",
    "python-socks[asyncio]>=2.4.0",
    "prompt-toolkit>=3.0.0",
+    "mcp>=1.0.0",
+    "json-repair>=0.30.0",
 ]

 [project.optional-dependencies]