Antigravity PDF MCP Server

A powerful Model Context Protocol (MCP) server that enables intelligent document ingestion and querying capabilities for AI agents and IDEs. This server allows you to build a persistent knowledge base from PDFs, Markdown, and Text files, and query them using advanced hybrid search techniques.

Features

• Multi-Format Ingestion: Support for .pdf, .md, and .txt files.
• Smart Chunking: Recursive character splitting preserves document structure (paragraphs, headers).
• Persistent Storage: Uses SQLite (antigravity.db) to store documents and vectors across restarts.
• Advanced Retrieval:
  • Hybrid Search: Combines TF-IDF (keyword) and OpenAI Embeddings (semantic) using Reciprocal Rank Fusion (RRF).
  • Filtering: Scope searches to specific documents.
  • Citations: Returns page numbers (e.g., [Page 5]) for easy verification.
• User Experience: Real-time progress notifications during ingestion.
• MCP Protocol: Fully compliant with the Model Context Protocol over Stdio.

Prerequisites

• Node.js (v18 or higher)
• npm

Installation

1. Clone the repository:

   git clone <repository-url>
   cd antigravity-pdf-mcp
   

2. Install dependencies:

   npm install
   

3. Build the project:

   npm run build
   

Configuration

To enable Semantic Search (Embeddings), create a .env file in the root directory:

OPENAI_API_KEY=sk-your-api-key-here

If no API key is provided, the server will fallback to local TF-IDF search only.

Tools

The server exposes the following MCP tools:

• ingest_document: Ingest a file (PDF, TXT, MD) into the knowledge base.
  • path: Absolute path to the file.
• query_knowledge_base: Search the knowledge base.
  • query: The search query.
  • document_id (Optional): Filter results to a specific document ID.
• list_documents: List all ingested documents.
• reset_library: Clear the entire database.
• ingest_pdf (Deprecated): Alias for ingest_document.

Usage with IDEs

This server uses the Stdio transport, making it compatible with any MCP-compliant client or IDE.

Antigravity IDE

1. Open Settings > MCP Servers.
2. Click Add Server.
3. Configure the server:
   • Name: antigravity-pdf
   • Command: node
   • Arguments:

     /absolute/path/to/antigravity-pdf-mcp/dist/server.js
     

   • Environment Variables:
     • OPENAI_API_KEY: Your OpenAI API key.

VSCode / Claude Desktop

Add to your MCP configuration file (e.g., claude_desktop_config.json):

{
  "mcpServers": {
    "antigravity-pdf": {
      "command": "node",
      "args": [
        "/absolute/path/to/antigravity-pdf-mcp/dist/server.js"
      ],
      "env": {
        "OPENAI_API_KEY": "your-api-key-if-needed"
      }
    }
  }
}

Contributing

1. Fork & Clone: Clone your fork locally.
2. Branch: Create a feature branch (git checkout -b feature/amazing-feature).
3. Develop: Make your changes.
4. Verify:
   • Run npm run build to check for errors.
   • Use npx ts-node verify_ux.ts to test ingestion and retrieval.
5. Commit & Push: Push changes to your fork.
6. Pull Request: Open a PR against the main repository.

License

MIT