一个桥接包，实现模型上下文协议（MCP）与 AI SDK 之间的无缝集成，实现 MCP 服务器与 AI 模型之间的高效通信和工具执行。

特色

• MCP服务器与AI SDK之间的无缝集成
• 支持多种MCP服务器类型（Node.js、Python、UVX）
• 多服务器支持，配置独立
• 通过[[T0]实现灵活配置]
• 支持TypeScript，支持完整的类型定义
• 稳健的错误处理和日志记录
• 易用的工具执行API

安装

快速启动

1. 在你的项目根创建一个 mcp.config.json 文件：

2. 导入并在代码中使用桥接：

配置

mcp.config.json 文件支持多个服务器和通信模式。每个服务器都可以独立配置。

服务器配置示例：

推特MCP服务器

火爬服务器

SSE 服务器

服务器模式

桥接器支持不同的通信模式：

1. stdio 模式（默认）

• 通过标准输入/输出实现直接通信
• 最适合简单集成和本地开发
• 低延迟和最小的设置需求

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"
      }
    }
  }
}

2. 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

{