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https://gitee.com/wanwujie/deer-flow
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74d4a16492
Add comprehensive MCP integration using langchain-mcp-adapters to enable pluggable external tools from MCP servers. Features: - MCP server configuration via mcp_config.json - Automatic lazy initialization for seamless use in both FastAPI and LangGraph Studio - Support for multiple MCP servers (filesystem, postgres, github, brave-search, etc.) - Environment variable resolution in configuration - Tool caching mechanism for optimal performance - Complete documentation and setup guide Implementation: - Add src/mcp module with client, tools, and cache components - Integrate MCP config loading in AppConfig - Update tool system to include MCP tools automatically - Add eager initialization in FastAPI lifespan handler - Add lazy initialization fallback for LangGraph Studio Dependencies: - Add langchain-mcp-adapters>=0.1.0 Documentation: - Add MCP_SETUP.md with comprehensive setup guide - Update CLAUDE.md with MCP system architecture - Update config.example.yaml with MCP configuration notes - Update README.md with MCP setup instructions Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
86 lines
2.7 KiB
Python
86 lines
2.7 KiB
Python
"""Cache for MCP tools to avoid repeated loading."""
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import asyncio
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import logging
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from langchain_core.tools import BaseTool
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logger = logging.getLogger(__name__)
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_mcp_tools_cache: list[BaseTool] | None = None
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_cache_initialized = False
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_initialization_lock = asyncio.Lock()
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async def initialize_mcp_tools() -> list[BaseTool]:
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"""Initialize and cache MCP tools.
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This should be called once at application startup.
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Returns:
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List of LangChain tools from all enabled MCP servers.
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"""
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global _mcp_tools_cache, _cache_initialized
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async with _initialization_lock:
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if _cache_initialized:
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logger.info("MCP tools already initialized")
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return _mcp_tools_cache or []
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from src.mcp.tools import get_mcp_tools
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logger.info("Initializing MCP tools...")
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_mcp_tools_cache = await get_mcp_tools()
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_cache_initialized = True
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logger.info(f"MCP tools initialized: {len(_mcp_tools_cache)} tool(s) loaded")
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return _mcp_tools_cache
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def get_cached_mcp_tools() -> list[BaseTool]:
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"""Get cached MCP tools with lazy initialization.
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If tools are not initialized, automatically initializes them.
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This ensures MCP tools work in both FastAPI and LangGraph Studio contexts.
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Returns:
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List of cached MCP tools.
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"""
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global _cache_initialized
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if not _cache_initialized:
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logger.info("MCP tools not initialized, performing lazy initialization...")
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try:
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# Try to initialize in the current event loop
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loop = asyncio.get_event_loop()
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if loop.is_running():
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# If loop is already running (e.g., in LangGraph Studio),
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# we need to create a new loop in a thread
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import concurrent.futures
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with concurrent.futures.ThreadPoolExecutor() as executor:
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future = executor.submit(asyncio.run, initialize_mcp_tools())
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future.result()
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else:
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# If no loop is running, we can use the current loop
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loop.run_until_complete(initialize_mcp_tools())
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except RuntimeError:
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# No event loop exists, create one
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asyncio.run(initialize_mcp_tools())
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except Exception as e:
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logger.error(f"Failed to lazy-initialize MCP tools: {e}")
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return []
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return _mcp_tools_cache or []
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def reset_mcp_tools_cache() -> None:
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"""Reset the MCP tools cache.
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This is useful for testing or when you want to reload MCP tools.
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"""
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global _mcp_tools_cache, _cache_initialized
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_mcp_tools_cache = None
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_cache_initialized = False
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logger.info("MCP tools cache reset")
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