MCP Documentation Server

@andrea9293

Basic information

About MCP Documentation Server

MCP Documentation Server - Bridge the AI Knowledge Gap.

MCP Documentation Server config

Add this server to your MCP-compatible client using the configuration below.

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

MCP Documentation Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

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

Frequently asked questions

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`.

Comments

More Memory & Knowledge MCP servers

Memory

modelcontextprotocol

Model Context Protocol Servers

88.1K

LoreKeeper RPG (lorekeeper.com)

LoreKeeper Ltd

Mess in, magic out: pour in your D&D and TTRPG notes and LoreKeeper keeps them as a private store for your world. Ask Claude or ChatGPT about it, or build a sourcebook.

Agimem

Persistent memory for AI agents. Hosted MCP server with capsule-scoped key/value storage, tags, TTL expiration, bulk ops, and RBAC.

Tempreon

Person-owned, portable AI memory served over MCP. Your knowledge, preferences, and decisions — captured in one assistant, available in all of them.

Takibi Base

Deian Isac

Ask your Takibi Base collections anything; get answers with cited passages and a support score.