Unified MCP Client Library

🌐 MCP Client is the open-source way to connect any LLM to any MCP server in TypeScript/Node.js, letting you build custom agents with tool access without closed-source dependencies.

💡 Let developers easily connect any LLM via LangChain.js to tools like web browsing, file operations, 3D modeling, and more.

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✨ Key Features

Feature	Description
🔄 Ease of use	Create an MCP-capable agent in just a few lines of TypeScript.
🤖 LLM Flexibility	Works with any LangChain.js-supported LLM that supports tool calling.
🌐 HTTP Support	Direct SSE/HTTP connection to MCP servers.
⚙️ Dynamic Server Selection	Agents select the right MCP server from a pool on the fly.
🧩 Multi-Server Support	Use multiple MCP servers in one agent.
🛡️ Tool Restrictions	Restrict unsafe tools like filesystem or network.
🔧 Custom Agents	Build your own agents with LangChain.js adapter or implement new adapters.

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🚀 Quick Start

Requirements

• Node.js 22.0.0 or higher
• npm, yarn, or pnpm (examples use pnpm)

Installation

# Install from npm
npm install mcp-use
# LangChain.js and your LLM provider (e.g., OpenAI)
npm install langchain @langchain/openai dotenv

Create a .env:

OPENAI_API_KEY=your_api_key

Basic Usage

import { ChatOpenAI } from '@langchain/openai'
import { MCPAgent, MCPClient } from 'mcp-use'
import 'dotenv/config'

async function main() {
  // 1. Configure MCP servers
  const config = {
    mcpServers: {
      playwright: { command: 'npx', args: ['@playwright/mcp@latest'] }
    }
  }
  const client = MCPClient.fromDict(config)

  // 2. Create LLM
  const llm = new ChatOpenAI({ modelName: 'gpt-4o' })

  // 3. Instantiate agent
  const agent = new MCPAgent({ llm, client, maxSteps: 20 })

  // 4. Run query
  const result = await agent.run('Find the best restaurant in Tokyo using Google Search')
  console.log('Result:', result)
}

main().catch(console.error)

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📂 Configuration File

You can store servers in a JSON file:

{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": ["@playwright/mcp@latest"]
    }
  }
}

Load it:

import { MCPClient } from 'mcp-use'

const client = MCPClient.fromConfigFile('./mcp-config.json')

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📚 Examples

We provide a comprehensive set of examples demonstrating various use cases. All examples are located in the examples/ directory with a dedicated README.

Running Examples

# Install dependencies
npm install

# Run any example
npm run example:airbnb      # Search accommodations with Airbnb
npm run example:browser     # Browser automation with Playwright
npm run example:chat        # Interactive chat with memory
npm run example:filesystem  # File system operations
npm run example:http        # HTTP server connection
npm run example:everything  # Test MCP functionalities
npm run example:multi       # Multiple servers in one session

Example Highlights

• Browser Automation: Control browsers to navigate websites and extract information
• File Operations: Read, write, and manipulate files through MCP
• Multi-Server: Combine multiple MCP servers (Airbnb + Browser) in a single task
• Sandboxed Execution: Run MCP servers in isolated E2B containers
• OAuth Flows: Authenticate with services like Linear using OAuth2

See the examples README for detailed documentation and prerequisites.

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🔄 Multi-Server Example

const config = {
  mcpServers: {
    airbnb: { command: 'npx', args: ['@openbnb/mcp-server-airbnb'] },
    playwright: { command: 'npx', args: ['@playwright/mcp@latest'] }
  }
}
const client = MCPClient.fromDict(config)
const agent = new MCPAgent({ llm, client, useServerManager: true })
await agent.run('Search Airbnb in Barcelona, then Google restaurants nearby')

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🔒 Tool Access Control

const agent = new MCPAgent({
  llm,
  client,
  disallowedTools: ['file_system', 'network']
})

👥 Contributors

Zane	Pietro Zullo

📜 License

MIT © Zane