quarry

punt-labs/quarry

★ 1 stars Python 🤖 AI/LLM Updated today

Locally hosted semantic search for AI agents. 20+ document formats, hybrid search, agent memory, zero cloud dependencies. MCP server + CLI.

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Quick Install

Copy the config for your editor. Some servers may need additional setup — check the README.

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "quarry": {
      "command": "uvx",
      "args": [
        "quarry"
      ]
    }
  }
}

Or install with pip: pip install quarry

README Excerpt

> Local semantic search for AI agents and humans. Quarry indexes documents in 20+ formats, embeds them with a local ONNX model (snowflake-arctic-embed-m-v1.5, 768-dim), stores vectors in LanceDB, and serves semantic search to Claude Code, Claude Desktop, and the CLI. Everything runs locally — no API keys, no cloud accounts. The embedding model (~120 MB int8) downloads once on first use. CUDA GPUs are auto-detected for faster inference.

Tools (16)

CHUNK_MAX_CHARSCHUNK_OVERLAP_CHARSQUARRY_API_KEYQUARRY_PROVIDERQUARRY_ROOTdeletederegister_directoryfindingestlistregister_directoryremembershowstatussync_all_registrationsuse

Topics

betaclaude-code-pluginmcp-serverocrvector-search

quarry

Quick Install

README Excerpt

Tools (16)

Topics

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