Mcp Documentation Server

Name: Mcp Documentation Server
Author: andrea9293

@andrea9293

リポジトリ

Mcp Documentation Server について

MCP Documentation Server - Bridge the AI Knowledge Gap.

#documentation #rag #knowledge

基本情報

カテゴリ

メモリとナレッジ

トランスポート

stdio

公開者

andrea9293

投稿者

Andrea Bravaccino

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": {
    "documentation": {
      "command": "npx",
      "args": [
        "-y",
        "@andrea9293/mcp-documentation-server"
      ]
    }
  }
}

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 Documentation Server?

A TypeScript-based Model Context Protocol (MCP) server that provides local-first document management and semantic search. Documents are stored in an embedded Orama vector database with hybrid search (full‑text + vector), intelligent chunking, and local AI embeddings — no external database or cloud service required.

How to use MCP Documentation Server?

Configure an MCP client (e.g., Claude Desktop) to run npx -y @andrea9293/mcp-documentation-server. The web UI starts automatically on port 3080. Use tools like add_document, search_all_documents, and process_uploads to manage and search documents. All environment variables are optional.

Key features of MCP Documentation Server

Local-first document management and semantic search
Hybrid full-text and vector search via Orama
AI-powered search with optional Gemini API key
Built-in web dashboard with drag-drop file uploads
Parent‑child chunking for context‑preserving retrieval
LRU embedding cache and streaming file reader

Use cases of MCP Documentation Server

Indexing project documentation for instant semantic lookup
Searching across code comments, markdown files, and PDFs
Providing LLMs with richer context via neighboring chunk retrieval
Managing a personal knowledge base without cloud dependencies
Uploading and processing .txt, .md, or .pdf files in bulk

FAQ from MCP Documentation Server

Where is data stored?

All data resides in ~/.mcp-documentation-server/ (or a custom path via MCP_BASE_DIR). No external database or cloud service is used.

Is an external database or cloud service required?

No. The embedded Orama vector database runs locally; all embeddings are computed on‑device with Transformers.js.

Do I need a Gemini API key?

No. Without GEMINI_API_KEY, only local embedding‑based search tools are available. The AI‑powered search (search_documents_with_ai) requires the key.

Can I change the embedding model after adding documents?

Yes, but changing MCP_EMBEDDING_MODEL requires re‑adding all documents because embeddings from different models are incompatible. The Orama database is recreated automatically when the vector dimension changes.

How do I access the web UI?

The web UI starts automatically on port 3080 when the MCP server launches. Open http://localhost:3080. To run it standalone (without the MCP server), use npm run web or npm run web:build.