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mcp-documentation-server

by andrea9293·313·Score 52

A TypeScript MCP server for local document management with semantic search using Orama vector database and optional Gemini AI integration.

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Overview

The MCP Documentation Server is a sophisticated tool for managing documents locally with advanced search capabilities. It uses an embedded Orama vector database for hybrid full-text and vector similarity search, with intelligent parent-child chunking to preserve context. The server includes a built-in web UI for document management and offers optional AI-powered search through Google Gemini integration. All data is stored locally in ~/.mcp-documentation-server/ with no external dependencies required.

Try asking AI

After installing, here are 5 things you can ask your AI assistant:

you:Managing and searching technical documentation and API references
you:Creating a knowledge base for internal company documentation
you:Personal document organization with semantic search capabilities
you:What file formats does the server support?
you:Is the web UI optional?

When to choose this

Choose this server when you need local-first document management with semantic search capabilities, especially when working with sensitive data that cannot be stored in cloud services.

When NOT to choose this

Avoid this if you need multi-user authentication or enterprise-level features like collaborative editing, as it's designed primarily for single-user local use.

Tools this server exposes

12 tools extracted from the README
  • add_document

    Add a document (title, content, optional metadata)

  • list_documents

    List all documents with metadata and content preview

  • get_document

    Retrieve the full content of a document by ID

  • delete_document

    Remove a document, its chunks, database entries, and associated files

  • process_uploads

    Process all files in the uploads folder (chunking + embeddings)

  • get_uploads_path

    Returns the absolute path to the uploads folder

  • list_uploads_files

    Lists files in the uploads folder with size and format info

  • get_ui_url

    Returns the Web UI URL (e.g. http://localhost:3080)

  • search_documents

    Semantic vector search within a specific document

  • search_all_documents

    Hybrid (full-text + vector) cross-document search

  • get_context_window

    Returns a window of chunks around a given chunk index

  • search_documents_with_ai

    AI-powered search using Gemini (requires GEMINI_API_KEY)

Comparable tools

semantic-search-mcpvector-mcpchroma-mcpembeddings-mcp

Installation

Installation

  1. Configure your MCP client (e.g., Claude Desktop, VS Code):
{
  "mcpServers": {
    "documentation": {
      "command": "npx",
      "args": [
        "-y",
        "@andrea9293/mcp-documentation-server"
      ],
      "env": {
        "MCP_BASE_DIR": "/path/to/workspace",
        "GEMINI_API_KEY": "your-api-key-here",
        "MCP_EMBEDDING_MODEL": "Xenova/all-MiniLM-L6-v2",
        "START_WEB_UI": "true",
        "WEB_PORT": "3080"
      }
    }
  }
}
  1. Install the package:
npm install -g @andrea9293/mcp-documentation-server

FAQ

What file formats does the server support?
The server supports .txt, .md, and .pdf files for upload and processing.
Is the web UI optional?
Yes, you can disable the web UI by setting START_WEB_UI=false in your environment configuration.

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Last updated · Auto-generated from public README + GitHub signals.