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docs-mcp-server MCP Server

@xinlei413

代码仓库

基本信息

分类

记忆与知识

许可证

MIT

传输方式

stdio

作者

xinlei413

关于 docs-mcp-server MCP Server

暂无概览

docs-mcp-server MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "MCP-DOC-Server-OpenRouter": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "\\"
      ]
    }
  }
}

docs-mcp-server MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is docs-mcp-server?

docs-mcp-server is an MCP server that fetches, indexes, and searches third‑party package documentation from multiple sources (websites, GitHub, npm, PyPI, local files). It processes content into chunks, supports full‑text search via SQLite FTS5, and integrates with OpenRouter API for chat/completions. Vector embeddings are currently disabled, leaving only full‑text search and chat/completions active.

How to use docs-mcp-server?

Run the server via Docker (docker run ... ghcr.io/arabold/docs-mcp-server:latest) or npx (npx -y --package=@arabold/docs-mcp-server docs-server), configured with your MCP client (e.g., Claude, Cline, Roo). An OpenAI API key is required. Use MCP tools such as scrape_docs, search_docs, and list_libraries, or use the included CLI (docs-cli).

Key features of docs-mcp-server

  • Versatile scraping: websites, GitHub, npm, PyPI, local files
  • Asynchronous job handling for scraping and indexing
  • Full‑text search with SQLite FTS5
  • OpenRouter API integration for chat/completions
  • Multiple embedding providers supported (currently disabled)
  • Simple deployment via Docker or npx

Use cases of docs-mcp-server

  • Index documentation of a library and search it via AI assistant
  • Fetch docs from multiple sources (web, GitHub, package registries)
  • Manage different versions of library documentation
  • Use chat/completions to answer questions about scraped content

常见问题

1

Are embeddings/vector search still available?

No. The current version has removed all embedding functionality. Only full‑text search and chat/completions are provided.

2

How do I run the server?

Use Docker with the image `ghcr.io/arabold/docs-mcp-server:latest` and set the required `OPENAI_API_KEY` environment variable. Alternatively, run via npx: `npx -y --package=@arabold/docs-mcp-server docs-server`.

3

Where is the indexed data stored?

Data is stored in an SQLite database inside the container’s `/data` directory. Persist it by mounting a Docker volume (e.g., `-v docs-mcp-data:/data`). The npx mode uses a default location in your home directory.

4

What dependencies are required?

For Docker: only Docker itself. For npx: Node.js must be installed. An API key (e.g., OpenAI) is required for chat/completions and was needed for embeddings when enabled.

5

Can I use the OpenRouter API?

Yes. Set `OPENAI_API_KEY` to your OpenRouter API key and optionally `OPENAI_API_BASE` to `https://openrouter.ai/api/v1`. Many models are supported (GPT‑4.1, Claude, Gemini, etc.).

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