Antigravity PDF

Provides ingest of PDFs, MDs, and TXT into a persistent knowledge base with hybrid search and page-cited results.

typescript

1

GitHub Stars

typescript

Language

3 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "asoluka-antigravity-pdf-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/antigravity-pdf-mcp/dist/server.js"
      ],
      "env": {
        "OPENAI_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Antigravity PDF MCP Server lets you build a persistent knowledge base from PDFs, Markdown, and text files and query it using advanced hybrid search. It integrates with MCP-enabled clients and IDEs over Stdio, provides real-time ingestion progress, and stores documents and their embeddings in a local SQLite database for reliable restarts and quick access.

How to use

You connect to the server from any MCP-enabled client or IDE using Stdio transport. Ingest documents such as PDFs, Markdown, and TXT files to populate a searchable knowledge base. Then issue queries to retrieve relevant passages with page citations for easy verification. Use document filtering to focus results on a specific file, if needed. Expect real-time feedback during ingestion and fast hybrid search that combines keyword matching with semantic embeddings.

Typical usage flow:

How to install

Prerequisites you need before installation are Node.js version 18 or higher and npm.

# 1. Clone the repository
git clone <repository-url>
cd antigravity-pdf-mcp

# 2. Install dependencies
npm install

# 3. Build the project
npm run build

Additional setup and usage notes

Semantic search (OpenAI embeddings) can be enabled by providing an API key. If no key is supplied, the server falls back to local TF-IDF search only.

OPENAI_API_KEY=sk-your-api-key-here

Configuration

To enable Embeddings, create an environment file in the project root with your API key. The server uses this key when available and otherwise uses keyword-only search.

MCP integration and client setup

The server communicates via the MCP over Stdio transport, so your MCP client or IDE can connect directly using standard MCP patterns.

Available tools

ingest_document

Ingest a file (PDF, TXT, MD) into the knowledge base. Provide the absolute path to the file.

query_knowledge_base

Search the knowledge base with a query. Optional filter by document_id to limit results to a specific document.

list_documents

List all ingested documents currently stored in the library.

reset_library

Clear the entire knowledge base, removing all documents and vectors.

ingest_pdf

Deprecated alias for ingest_document; use ingest_document instead.