LanceDB Node.js Vector Search

What it is

A Node.js vector search server over LanceDB. Queries are embedded locally by Ollama and matched against documents already stored in a LanceDB directory, so both the index and the embedding model stay on your machine.

What you get

• Vector similarity search against stored documents, with results and their similarity scores
• A custom embedding function that calls Ollama and returns embeddings of 768 dimensions, formatted for LanceDB
• A test script you can run before wiring anything up, to confirm the database and the embedding endpoint both answer

Requirements

Node.js v14 or later, a LanceDB storage directory you can read and write, and Ollama running locally with the nomic-embed-text model — the embedding endpoint is http://localhost:11434/api/embeddings. Install with pnpm install. The client launches dist/index.js with node and a --db-path argument pointing at your LanceDB storage. No cloud account and no API key.

Setup effort

Build from source — git clone https://github.com/vurtnec/mcp-LanceDB-node

Requires

• Node.js 14 or later
• Ollama running locally with the nomic-embed-text model
• A LanceDB storage directory with read/write permissions

Where it runs

The documented client runs the server on your machine.