Full-Stack MCP Framework

mcp-use provides everything you need to build with Model Context Protocol
MCP servers, MCP clients and AI agents in 6 lines of code, in both Python and TypeScript.

• 🤖 MCP Agents - AI agents that can use tools and reason across steps
• 🔌 MCP Clients - Connect any LLM to any MCP server
• 🛠️ MCP Servers - Build your own MCP servers
• 🔍 MCP Inspector - Web-based debugger for MCP servers
• 🎨 MCP-UI Resources - Build ChatGPT apps with interactive widgets

Create an AI agent that can use MCP tools to accomplish complex tasks.

pip install mcp-use langchain-openai

import asyncio from langchain_openai import ChatOpenAI from mcp_use import MCPAgent, MCPClient async def main(): # Configure MCP server config = { "mcpServers": { "filesystem": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"] } } } client = MCPClient.from_dict(config) llm = ChatOpenAI(model="gpt-4o") agent = MCPAgent(llm=llm, client=client) result = await agent.run("List all files in the directory") print(result) asyncio.run(main())

→ Full Python Agent Documentation

npm install mcp-use @langchain/openai

import { ChatOpenAI } from "@langchain/openai"; import { MCPAgent, MCPClient } from "mcp-use"; async function main() { // Configure MCP server const config = { mcpServers: { filesystem: { command: "npx", args: ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"], }, }, }; const client = MCPClient.fromDict(config); const llm = new ChatOpenAI({ modelName: "gpt-4o" }); const agent = new MCPAgent({ llm, client }); const result = await agent.run("List all files in the directory"); console.log(result); } main();

→ Full TypeScript Agent Documentation

Connect to MCP servers directly without an AI agent for programmatic tool access.

import asyncio from mcp_use import MCPClient async def main(): config = { "mcpServers": { "calculator": { "command": "npx", "args": ["-y", "@modelcontextprotocol/server-everything"] } } } client = MCPClient.from_dict(config) await client.create_all_sessions() session = client.get_session("calculator") result = await session.call_tool(name="add", arguments={"a": 5, "b": 3}) print(f"Result: {result.content[0].text}") await client.close_all_sessions() asyncio.run(main())

→ Python Client Documentation

import { MCPClient } from "mcp-use"; async function main() { const config = { mcpServers: { calculator: { command: "npx", args: ["-y", "@modelcontextprotocol/server-everything"], }, }, }; const client = new MCPClient(config); await client.createAllSessions(); const session = client.getSession("calculator"); const result = await session.callTool("add", { a: 5, b: 3 }); console.log(`Result: ${result.content[0].text}`); await client.closeAllSessions(); } main();

→ TypeScript Client Documentation

Build your own MCP server with custom tools, resources, and prompts.

npx create-mcp-use-app my-server cd my-server npm install

import { MCPServer, text } from "mcp-use/server"; import { z } from "zod"; const server = new MCPServer({ name: "my-server", version: "1.0.0", description: "My custom MCP server", }); // Define a tool server.tool( { name: "get_weather", description: "Get weather for a city", schema: z.object({ city: z.string().describe("City name"), }), }, async ({ city }) => { return text(`Temperature: 72°F, Condition: sunny, City: ${city}`); } ); // Start server with auto-inspector server.listen(3000); // 🎉 Inspector at http://localhost:3000/inspector

→ Full TypeScript Server Documentation

Coming Soon! For now, please use the TypeScript implementation to create MCP servers.

Debug and test your MCP servers with the interactive web-based inspector.

When you create a server with mcp-use, the inspector is automatically available:

server.listen(3000); // Inspector automatically at: http://localhost:3000/inspector

Inspect any MCP server via CLI:

npx @mcp-use/inspector --url http://localhost:3000/sse

Features:

• 🔍 Test tools interactively with live execution
• 📊 Monitor connection status and server health
• 🔐 Handle OAuth flows automatically
• 💾 Persistent sessions with localStorage

→ Full Inspector Documentation

• Web Browsing with Playwright - Automate browser tasks
• Multi-Server Setup - Use multiple MCP servers together
• Streaming Responses - Real-time agent output
• UI Widgets - Build interactive React components
• AI SDK Integration - Vercel AI SDK for Next.js apps

• 📘 Python Documentation - Complete Python guide
• 📗 TypeScript Documentation - Complete TypeScript guide
• 🔍 Inspector Documentation - Inspector guide
• 🌐 Online Docs - Full online documentation

This monorepo contains multiple packages for both Python and TypeScript:

Package	Description	Version
mcp-use	Complete MCP client and agent library

Package	Description	Version
mcp-use	Core framework for clients, agents, and servers
@mcp-use/cli	Build tool with hot reload and auto-inspector
@mcp-use/inspector	Web-based debugger for MCP servers
create-mcp-use-app	Project scaffolding tool

mcp-use/ ├── libraries/ │ ├── python/ → Python implementation │ │ ├── mcp_use/ → Core library │ │ ├── examples/ → Python examples │ │ └── docs/ → Python documentation │ │ │ └── typescript/ → TypeScript implementation │ └── packages/ │ ├── mcp-use/ → Core framework │ ├── cli/ → Build tool │ ├── inspector/ → Web inspector │ └── create-mcp-use-app/ → Scaffolding └── README.md → This file 

Build everything from AI agents to servers - not just clients. Create the full MCP ecosystem in your preferred language.

Choose Python for ML/data workflows or TypeScript for web applications. Same great features, different languages.

Includes observability, streaming, multi-server support, sandboxing, and tool access controls out of the box.

Hot reload, TypeScript/Python type safety, built-in inspector, and comprehensive documentation.

MIT licensed and community-driven. Contribute, fork, or extend as needed.

• 💬 Discord: Join our community
• 🐛 GitHub Issues: Report bugs or request features
• 📖 Documentation: docs.mcp-use.com
• 🌐 Website: mcp-use.com
• 🐦 Twitter: Follow @pietrozullo and @pederzh

MIT © MCP-Use Contributors

We love contributions! Check out our contributing guidelines:

• Python Contributing Guide
• TypeScript Contributing Guide

If you use MCP-Use in your research or project, please cite:

@software{mcp_use2025, author = {Zullo, Pietro and Contributors}, title = {MCP-Use: Complete MCP Ecosystem for Python and TypeScript}, year = {2025}, publisher = {GitHub}, url = {https://github.com/mcp-use/mcp-use} }

Thanks to all our amazing contributors!

1. Pietro (@pietrozullo)
2. Luigi (@pederzh)
3. Enrico (@tonxxd)