AISDK MCP Bridge

A bridge package that enables seamless integration between the Model Context Protocol (MCP) and AI SDK, allowing for efficient communication and tool execution between MCP servers and AI models.

Features

• Seamless integration between MCP servers and AI SDK
• Support for various MCP server types (Node.js, Python, UVX)
• Multi-server support with independent configuration
• Flexible configuration through mcp.config.json
• TypeScript support with full type definitions
• Robust error handling and logging
• Easy-to-use API for tool execution

Installation

npm install aisdk-mcp-bridge

Quick Start

1. Create an mcp.config.json file in your project root:

{
  "mcpServers": {
    "twitter-mcp": {
      "command": "npx",
      "args": ["-y", "@enescinar/twitter-mcp"],
      "env": {
        "API_KEY": "your-twitter-api-key",
        "API_SECRET_KEY": "your-twitter-api-secret",
        "ACCESS_TOKEN": "your-twitter-access-token",
        "ACCESS_TOKEN_SECRET": "your-twitter-access-token-secret"
      }
    },
    "firecrawl": {
      "command": "npx",
      "args": ["-y", "mcp-server-firecrawl"],
      "env": {
        "FIRE_CRAWL_API_KEY": "your-firecrawl-api-key",
        "FIRE_CRAWL_API_URL": "https://api.firecrawl.com"
      }
    }
  }
}

1. Import and use the bridge in your code:

import { generateText } from 'ai';
import { google } from '@ai-sdk/google';
import { getMcpTools, cleanupMcp, initializeMcp } from 'aisdk-mcp-bridge';
import dotenv from 'dotenv';
dotenv.config();

async function main() {
  try {
    // Initialize MCP
    await initializeMcp({ debug: true });

    // Get tools from all servers
    const allTools = await getMcpTools({ debug: true });

    // Or get tools from a specific server
    const twitterTools = await getMcpTools({
      debug: true,
      serverName: 'twitter-mcp',
    });

    // Use tools with AI SDK
    const result = await generateText({
      model: google('gemini-1.5-pro'),
      messages: [
        {
          role: 'system',
          content:
            'You are an AI assistant that uses various tools to help users.',
        },
        {
          role: 'user',
          content: 'Your task description here',
        },
      ],
      tools: twitterTools, // or allTools for all available tools
    });

    console.log('Result:', result.text);
  } finally {
    // Clean up resources
    await cleanupMcp();
  }
}

main().catch(error => {
  console.error('Error:', error);
  process.exit(1);
});

Configuration

The mcp.config.json file supports multiple servers and communication modes. Each server can be configured independently.

Server Configuration Examples:

Twitter MCP Server

{
  "mcpServers": {
    "twitter-mcp": {
      "command": "npx",
      "args": ["-y", "@enescinar/twitter-mcp"],
      "env": {
        "API_KEY": "your-twitter-api-key",
        "API_SECRET_KEY": "your-twitter-api-secret",
        "ACCESS_TOKEN": "your-twitter-access-token",
        "ACCESS_TOKEN_SECRET": "your-twitter-access-token-secret"
      }
    }
  }
}

Firecrawl Server

{
  "mcpServers": {
    "firecrawl": {
      "command": "npx",
      "args": ["-y", "mcp-server-firecrawl"],
      "env": {
        "FIRE_CRAWL_API_KEY": "your-firecrawl-api-key",
        "FIRE_CRAWL_API_URL": "https://api.firecrawl.com"
      }
    }
  }
}

SSE Server

{
  "mcpServers": {
    "sse-server": {
      "command": "node",
      "args": ["./server.js"],
      "mode": "sse",
      "sseOptions": {
        "endpoint": "http://localhost:3000/events",
        "headers": {},
        "reconnectTimeout": 5000
      }
    }
  }
}

Server Modes

The bridge supports different communication modes:

1. stdio Mode (Default)

   • Direct communication through standard input/output
   • Best for simple integrations and local development
   • Low latency and minimal setup required

2. SSE Mode (Server-Sent Events)

   • Real-time, one-way communication from server to client
   • Ideal for streaming updates and long-running operations
   • Built-in reconnection handling

API Reference

Core Functions

initializeMcp(options?: InitOptions): Promise<void>

Initialize the MCP service with the provided options.

interface InitOptions {
  configPath?: string; // Path to mcp.config.json
  debug?: boolean; // Enable debug logging
}

getMcpTools(options?: ToolOptions): Promise<ToolSet>

Get AI SDK-compatible tools from MCP servers.

interface ToolOptions {
  debug?: boolean; // Enable debug logging
  serverName?: string; // Optional server name to get tools from a specific server
}

executeMcpFunction(serverName: string, functionName: string, args: Record<string, unknown>): Promise<MCPToolResult>

Execute a specific function on an MCP server directly.

// Example
const result = await executeMcpFunction('twitter-mcp', 'postTweet', {
  text: 'Hello from MCP!',
});

Core Types

MCPConfig (alias for MCPServersConfig)

Configuration type for MCP servers.

interface MCPConfig {
  mcpServers: {
    [key: string]: ServerConfig;
  };
}

ServerConfig

Configuration for individual MCP servers.

interface ServerConfig {
  command: string;
  args?: string[];
  env?: Record<string, string>;
  mode?: 'stdio' | 'sse';
  sseOptions?: {
    endpoint: string;
    headers?: Record<string, string>;
    reconnectTimeout?: number;
  };
}

MCPToolResult

Result type for MCP tool executions.

interface MCPToolResult {
  success: boolean;
  data?: unknown;
  error?: string;
}

cleanupMcp(): Promise<void>

Clean up MCP resources and close all server connections.

Error Handling

The bridge includes comprehensive error handling for:

• Server initialization failures
• Communication errors
• Tool execution failures
• Configuration issues
• Server connection issues

Logging

The bridge provides detailed logging through:

• mcp-tools.log: Server-side tool execution logs
• Console output for debugging and errors

Debug Logging

You can enable detailed debug logging by setting the DEBUG environment variable:

# Enable all debug logs
DEBUG=* npm start

# Enable MCP debug logs
DEBUG=mcp npm start

# Enable all MCP namespace logs
DEBUG=mcp:* npm start

Debug logs will show:

• Server initialization and shutdown events
• Tool registration and execution details
• Communication with MCP servers
• Schema conversions and validations
• Error details with stack traces
• Performance metrics and timing information

Log Types

The logging system supports three types of logs:

• info: General operational information
• debug: Detailed debugging information (requires DEBUG env variable)
• error: Error messages and stack traces (always logged)

Log File

All logs are written to logs/mcp-tools.log with the following format:

[TIMESTAMP] [TYPE] Message
{Optional JSON data}

Development

Prerequisites

• Node.js 20.x or higher
• npm 7.x or higher

Setup

1. Clone the repository
2. Install dependencies:

npm install

Testing

Run the test suite:

npm test

Run specific tests:

npm run test:twitter
npm run test:firecrawl

Contributing

We welcome contributions! Please see our Contributing Guide for details on:

• Setting up the development environment
• Coding standards
• Pull request process
• Adding new MCP servers

Please note that this project is released with a Code of Conduct. By participating in this project you agree to abide by its terms.

Support

For support:

1. Check the documentation
2. Search existing issues
3. Create a new issue if your problem persists

Changelog

See CHANGELOG.md for a list of changes and migration guides.

Security

For security issues, please email ravi@caw.tech instead of using the public issue tracker.

Authors

• Ravi Kiran - Initial work - @vrknetha

See also the list of contributors who participated in this project.

Acknowledgments

• AI SDK team for their excellent SDK
• MCP community for the protocol specification
• All contributors who have helped with the project

License

This project is licensed under the MIT License - see the LICENSE file for details.