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.

Core capabilities

🌐 Web UI

• Built-in Web Interface: A full-featured web dashboard starts automatically alongside the MCP server — no additional setup required
• Complete Tool Coverage: Every MCP tool is accessible from the browser: add/view/delete documents, semantic search, AI search, file uploads, and context window exploration
• Drag & Drop Uploads: Upload .txt, .md, and .pdf files directly from the browser
• Configurable: Disable with START_WEB_UI=false or change the port with WEB_PORT

🔍 Search & Intelligence

• Hybrid Search: Combined full-text and vector similarity powered by Orama, for both single-document and cross-document queries
• AI-Powered Search 🤖: Advanced document analysis with Google Gemini AI for contextual understanding and intelligent insights (optional, requires API key)
• Context Window Retrieval: Fetch surrounding chunks to provide LLMs with richer context

⚡ Performance & Architecture

• Orama Vector DB: Embedded search engine with zero native dependencies — replaces manual JSON storage and cosine similarity
• LRU Embedding Cache: Avoids recomputing embeddings for repeated content and queries
• Parent-Child Chunking: Documents are split into large context-preserving parent chunks and small precise child chunks for vector search — search results include both the matched fragment and the full surrounding context
• Streaming File Reader: Handles large files without high memory usage
• Automatic Migration: Legacy JSON documents are migrated to Orama on first startup — no manual intervention needed

📁 File Management

• Upload processing: Drop .txt, .md, or .pdf files into the uploads folder and process them with a single tool call
• Copy-based storage: Original files are backed up alongside the database
• Local-only storage: All data resides in ~/.mcp-documentation-server/

Quick Start

Configure an MCP client

Example configuration for an MCP client (e.g., Claude Desktop, VS Code):

Quick Start

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

Advanced with env vars (all vars are optional)

{
  "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",
      }
    }
  }
}

All environment variables are optional. Without GEMINI_API_KEY, only the local embedding-based search tools are available.

Web

... View full README on GitHub