Files
chatgpt-on-wechat/agent/tools/mcp/mcp_tool.py
ooaaooaa123 b2429ec30c feat(mcp): add MCP (Model Context Protocol) tool integration
Allows CowAgent to dynamically load tools from any MCP server at startup,
extending the agent from a fixed toolset to an open, extensible tool ecosystem.

## What's added

- `agent/tools/mcp/mcp_client.py`: lightweight JSON-RPC client supporting both
  stdio (subprocess) and SSE (HTTP) transports — zero extra dependencies
- `agent/tools/mcp/mcp_tool.py`: `McpTool` wraps a single MCP tool as a
  `BaseTool`, with dynamic name/description/params set at instance level
- `agent/tools/tool_manager.py`: new `_load_mcp_tools()` loads MCP servers at
  startup via `McpClientRegistry`; falls back gracefully on any error; no-op
  when `mcp_servers` is not configured
- `config.py`: registers `mcp_servers` in `available_setting` with inline docs

## Design

- No new dependencies — JSON-RPC implemented from scratch using stdlib only
- MCP clients are long-lived (initialized once, shared across tool calls)
- `McpClientRegistry` holds all subprocess handles and shuts them down cleanly
- Server init failures are non-fatal: logged as warnings, agent continues normally
- Zero overhead when `mcp_servers` is absent from config

## Config example

```json
"mcp_servers": [
  {
    "name": "filesystem",
    "type": "stdio",
    "command": "npx",
    "args": ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"]
  }
]
```

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-06 20:16:04 +08:00

32 lines
1.2 KiB
Python

from agent.tools.base_tool import BaseTool, ToolResult
from common.log import logger
class McpTool(BaseTool):
"""
将单个 MCP 工具包装为 BaseTool。
一个 MCP Server 可以提供多个工具,每个工具对应一个 McpTool 实例。
"""
def __init__(self, client, tool_schema: dict, server_name: str):
"""
:param client: 该工具所属的 McpClient 实例
:param tool_schema: MCP 返回的工具描述,格式:
{"name": str, "description": str, "inputSchema": dict}
:param server_name: Server 名称,用于日志
"""
self.client = client
self.server_name = server_name
self.name = tool_schema["name"]
self.description = tool_schema.get("description", "")
self.params = tool_schema.get("inputSchema", {})
def execute(self, params: dict) -> ToolResult:
logger.info(f"[McpTool] server={self.server_name} tool={self.name} params={params}")
try:
result = self.client.call_tool(self.name, params)
return ToolResult.success(result)
except Exception as e:
logger.error(f"[McpTool] server={self.server_name} tool={self.name} error: {e}")
return ToolResult.fail(str(e))