🌐 MCP-Use is the open source way to connectany LLM to any MCP server and build custom agents that have tool access, without using closed source or application clients.

• If you want to get started quickly, check outmcp-use.com website to build and deploy agents with your favorite MCP servers.
• Visit themcp-use docs to get started with mcp-use library.
• Python SDK:mcp-use
• TypeScript SDK:mcp-use-ts

mcp-use is an open source library that enables developers to connect any LLM to any MCP server, allowing the creation of custom agents with tool access without relying on closed-source or application-specific clients.

Here's a quick example of how you can usemcp-use:

importasynciofromlangchain_openaiimportChatOpenAIfrommcp-useimportMCPAgent,MCPClientasyncdefmain():client=MCPClient(config= {"mcpServers":{"playwright": {"command":"npx","args": ["@playwright/mcp@latest"],"env": {"DISPLAY":":1"}    }}})# Create LLMllm=ChatOpenAI(model="gpt-4o",api_key=...)# Create agent with toolsagent=MCPAgent(llm=llm,client=client,max_steps=30)# Run the queryresult=awaitagent.run("Find the best restaurant in San Francisco")if__name__=="__main__":asyncio.run(main())

➡️Create your own with our Builder

• 💻 Open Source: Connect any LLM to any MCP server without vendor lock-in.
• ⚙️ Flexible Configuration: Support for any MCP server through a simple configuration system.
• ⚙️ Easy Setup: Simple JSON-based configuration for MCP server integration.
• 🤖 Universal LLM Support: Compatible with any LangChain-supported LLM provider.
• 🔌 HTTP Connection: Connect to MCP servers running on specific HTTP ports for web-based integrations.
• 🔀 Dynamic Server Selection: Agents can dynamically choose the most appropriate MCP server for the task.

• 📥 Installation:Install mcp-use and set up your environment
• 📖 Configuration:Learn how to configure mcp-use with your MCP server

We are constantly working to improvemcp-use. Check out what we're planning and suggest new features!

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