vercel-ai-docs-mcp

A Model Context Protocol (MCP) server that provides AI-powered search and querying capabilities for the Vercel AI SDK documentation. This project enables developers to ask questions about the Vercel AI SDK and receive accurate, contextualized responses based on the official documentation.

[](https://modelcontextprotocol.io) [](https://www.typescriptlang.org/) [](https://nodejs.org/)

• Direct Documentation Search: Query the Vercel AI SDK documentation index directly using similarity search
• AI-Powered Agent: Ask natural language questions about the Vercel AI SDK and receive comprehensive answers
• Session Management: Maintain conversation context across multiple queries
• Automated Indexing: Includes tools to fetch, process, and index the latest Vercel AI SDK documentation

This system consists of several key components:

1. MCP Server: Exposes tools via the Model Context Protocol for integration with AI assistants
2. DocumentFetcher: Crawls and processes the Vercel AI SDK documentation
3. VectorStoreManager: Creates and manages the FAISS vector index for semantic search
4. AgentService: Provides AI-powered answers to questions using the Google Gemini model
5. DirectQueryService: Offers direct semantic search of the documentation

• Node.js 18+
• npm
• A Google API key for Gemini model access

Create a .env file in the project root with the following variables:

GOOGLE_GENERATIVE_AI_API_KEY=your-google-api-key-here

You'll need to obtain a Google Gemini API key from the Google AI Studio.

1. Clone the repository

   git