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IvanAmador/vercel-ai-docs-mcp

IvanAmador/vercel-ai-docs-mcp

📇 🏠 - AI-powered search and querying of the Vercel AI SDK documentation
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add vercel-ai-docs-mcp -- npx -y vercel-ai-docs-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
50 ★ · IvanAmador/vercel-ai-docs-mcp · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 10 个来源列出
评分构成
综合分 1,003 · 50 ★ · 10 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 IvanAmador/vercel-ai-docs-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

Vercel AI SDK Documentation MCP Agent

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

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.
Features
- **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
Architecture
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
Setup Instructions
Prerequisites
- Node.js 18+
- npm
- A Google API key for Gemini model access
Environment Variables
Create a .env file in the project root with the following variables:
You'll need to obtain a Google Gemini API key from the Google AI Studio.
Installation
1. Clone the repository
2. Install dependencies
3. Build the project
4. Build the documentation index
5. Start the MCP server
Integration with Claude Desktop
Claude Desktop is a powerful AI assistant that supports MCP servers. To connect the Vercel AI SDK Documentation MCP agent with Claude Desktop:
1. First, install Claude Desktop if you don't have it already.
2. Open Claude Desktop settings (via the application menu, not within the chat interface).
3. Navigate to the "Developer" tab and click "Edit Config".
4. Add the Vercel AI Docs MCP server to your configuration:
Make sure to replace:
- ABSOLUTE_PATH_TO_PROJECT with the actual path to your project folder
- your-google-api-key-here with your Google Gemini API key
5. Save the config file and restart Claude Desktop.
6. To verify the server is connected, look for the hammer 🔨 icon in the Claude chat interface.
For more detailed information about setting up MCP servers with Claude Desktop, visit the MCP Quickstart Guide.
Integration with Other MCP Clients
This MCP server is compatible with any client that implements the Model Context Protocol. Here are a few examples:
Cursor
Cursor is an AI-powered code editor that supports MCP servers. To integrate with Cursor:
1. Add a .cursor/mcp.json file to your project directory (for project-specific configuration) or a ~/.cursor/mcp.json file in your home directory (for global configuration).
2. Add the following to your configuration file:
来源
awesome · https://github.com/IvanAmador/vercel-ai-docs-mcp
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