punt-quarry
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.
Platforms: macOS, Linux
Quick Start
curl -fsSL https://raw.githubusercontent.com/punt-labs/quarry/35a4b33/install.sh | sh
Restart Claude Code, then:
> /ingest report.pdf # index a document (runs in background)
> /quarry status # after a moment, confirm it's there
> /find "what does the report say about margins" # search by meaning
Once installed, a plugin hook auto-indexes your current project directory on every session start — you don't need to /ingest your codebase manually.
Manual install (if you already have uv)
uv tool install punt-quarry
quarry install
quarry doctor
Verify before running
curl -fsSL https://raw.githubusercontent.com/punt-labs/quarry/35a4b33/install.sh -o install.sh
shasum -a 256 install.sh
cat install.sh
sh install.sh
Remote Server
Run quarry on a GPU server and connect from any Mac or Linux client over TLS.
Server (GPU host, serves remote clients):
export QUARRY_API_KEY=$(openssl rand -hex 32)
curl -fsSL https://raw.githubusercontent.com/punt-labs/quarry/35a4b33/install.sh | sh -s -- --network
Generates TLS certificates, binds daemon to 0.0.0.0, registers a systemd service, and prints a CA fingerprint. NVIDIA GPUs are auto-detected for CUDA inference.
Client (connects to remote server):
curl -fsSL https://raw.githubusercontent.com/punt-labs/quarry/35a4b33/install.sh | sh
quarry login <server-hostname> --api-key <token>
No special flag needed --- the default install runs a local daemon on localhost. quarry login redirects queries to the remote server over wss:// with TOFU certificate pinning.
Claude Desktop
Download punt-quarry.mcpb and double-click to install. Alternatively, quarry install configures Claude Desktop automatically.
Note: Uploaded files in Claude Desktop live in a sandbox that quarry cannot access. Use remember for uploaded content, or provide local file paths to ingest.
Features
- 20+ formats --- PDFs (with OCR for scanned pages), source code (AST-aware splitting), spreadsheets, presentations, HTML, Markdown, LaTeX, DOCX, images
- Semantic search --- retrieval is by meaning, not keyword. A query about "margins" finds passages about profitability even if they never use that word
- Daemon architecture --- one
quarry serve process loads the embedding model once and serves all Claude Code sessions via mcp-proxy over WebSocket
- Passive knowledge capture ---
quarry enable sets up three scoped collections per project: file sync, passive captures (web fetches + session transcripts), and per-agent memory. Captures are separated from the code index so research doesn't pollute code search
- Named databases --- isolated LanceDB directories with independent sync registries. Switch with
use for work/personal separation
- Research agent ---
researcher subagent combines quarry local search with web research, auto-ingests valuable findings
What It Looks Like
Ingest a document
> /ingest report.pdf
▶ Ingesting report.pdf (background)
Check what's indexed
> /quarry
▶ Database: default
Documents: 47
Chunks: 1,203
Size: 12.4 MB
Model: snowflake-arctic-embed-m-v1.5 (768-dim)
Search by meaning
> /find "what were the Q3 revenue figures"
▶ [report.pdf p.12 | text/.pdf] (similarity: 0.4521)
Third quarter revenue reached $142M, up 18% year-over-year,
driven primarily by expansion in the enterprise segment.
Gross margins improved to 71% from 68% in Q2.
Commands
Slash Commands (Claude Code)
