mcp-qdrant-docs MCP Server

Name: mcp-qdrant-docs MCP Server
Author: kazuph

@kazuph

リポジトリ

mcp-qdrant-docs MCP Server について

An MCP server that scrapes websites, indexes content into Qdrant, and provides a query tool.

基本情報

カテゴリ

データベース

ランタイム

node

トランスポート

stdio

公開者

kazuph

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-qdrant-docs": {
      "command": "npx",
      "args": [
        "@kazuph/mcp-qdrant-docs",
        "--start-url",
        "https://example-docs.com/",
        "--collection-name",
        "my-docs",
        "--limit",
        "50",
        "--debug"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is mcp-qdrant-docs MCP Server?

A TypeScript-based MCP server that scrapes website content, indexes it into a Qdrant vector database, and provides a tool to answer natural language questions about the indexed content. Designed for developers who want to query documentation or web pages using an AI assistant.

How to use mcp-qdrant-docs MCP Server?

Install globally with npm i -g @kazuph/mcp-qdrant-docs or use npx in your MCP client configuration. Configure in Claude Desktop’s claude_desktop_config.json by setting command, args, and environment variables such as DOCS_URL, QDRANT_URL, and COLLECTION_NAME. Then invoke the tool (e.g., ask_reactrouter_docs) with a natural language query.

Key features of mcp-qdrant-docs MCP Server

Scrapes websites and indexes content into Qdrant.
Dynamically generates a tool per website (e.g., ask_reactrouter_docs).
Embeds queries and searches Qdrant for relevant chunks.
Supports force reindexing and limits on pages scraped.
Configurable via CLI options and environment variables.

Use cases of mcp-qdrant-docs MCP Server

Ask questions about React Router documentation using natural language.
Query Hono.dev documentation content directly.
Interrogate Gradio.app LLMs documentation.
General Q&A over any website’s documentation.

FAQ from mcp-qdrant-docs MCP Server

What does the server do with scraped content?

It processes, chunks, and embeds the content using a sentence transformer model, then stores embeddings and chunks in a Qdrant collection specific to the website.

How do I configure the server for a new documentation site?

Set the DOCS_URL environment variable (or --start-url CLI option) and optionally QDRANT_URL, COLLECTION_NAME, and EMBEDDING_MODEL. Add an entry to your MCP client configuration file.

What are the dependencies/runtime requirements?

Requires Node.js and npm. The server needs access to a running Qdrant instance (default http://localhost:6333) and uses sentence transformer models from Hugging Face.

Where does the data live?

Scraped content and embeddings are stored in a Qdrant collection whose name is based on COLLECTION_NAME and the sanitized hostname of the scraped site.

What is the transport/auth method?

The server communicates via MCP protocol over stdio. No authentication is mentioned in the README.

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