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hannesrudolph/mcp-ragdocs

hannesrudolph/mcp-ragdocs

🐍 🏠 - Retrieve and process documentation through vector search to augment responses with relevant…
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官方说明RAG Documentation MCP Server An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
配置模板(请按你的客户端调整)
claude mcp add mcp-ragdocs -- npx -y mcp-ragdocs
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
265 ★ · hannesrudolph/mcp-ragdocs · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
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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
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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
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综合分 1,003 · 265 ★ · 10 个来源 · mcp
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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。
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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 hannesrudolph/mcp-ragdocs;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

RAG Documentation MCP Server

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

An MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
Features
- Vector-based documentation search and retrieval
- Support for multiple documentation sources
- Semantic search capabilities
- Automated documentation processing
- Real-time context augmentation for LLMs
Tools
search_documentation
Search through stored documentation using natural language queries. Returns matching excerpts with context, ranked by relevance.
**Inputs:**
- query (string): The text to search for in the documentation. Can be a natural language query, specific terms, or code snippets.
- limit (number, optional): Maximum number of results to return (1-20, default: 5). Higher limits provide more comprehensive results but may take longer to process.
list_sources
List all documentation sources currently stored in the system. Returns a comprehensive list of all indexed documentation including source URLs, titles, and last update times. Use this to understand what documentation is available for searching or to verify if specific sources have been indexed.
extract_urls
Extract and analyze all URLs from a given web page. This tool crawls the specified webpage, identifies all hyperlinks, and optionally adds them to the processing queue.
**Inputs:**
- url (string): The complete URL of the webpage to analyze (must include protocol, e.g., https://). The page must be publicly accessible.
- add_to_queue (boolean, optional): If true, automatically add extracted URLs to the processing queue for later indexing. Use with caution on large sites to avoid excessive queuing.
remove_documentation
Remove specific documentation sources from the system by their URLs. The removal is permanent and will affect future search results.
**Inputs:**
- urls (string[]): Array of URLs to remove from the database. Each URL must exactly match the URL used when the documentation was added.
list_queue
List all URLs currently waiting in the documentation processing queue. Shows pending documentation sources that will be processed when run_queue is called. Use this to monitor queue status, verify URLs were added correctly, or check processing backlog.
run_queue
Process and index all URLs currently in the documentation queue. Each URL is processed sequentially, with proper error handling and retry logic. Progress updates are provided as processing occurs. Long-running operations will process until the queue is empty or an unrecoverable error occurs.
clear_queue
Remove all pending URLs from the documentation processing queue. Use this to reset the queue when you want to start fresh, remove unwanted URLs, or cancel pending processing. This operation is immediate and permanent - URLs will need to be re-added if you want to process them later.
来源
awesome · https://github.com/hannesrudolph/mcp-ragdocs
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