punt-quarry
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@punt-quarryfind 'what does the report say about margins'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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/6f90f11/install.sh | shRestart 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 meaningOnce installed, a plugin hook auto-indexes your current project directory on every session start — you don't need to /ingest your codebase manually.
uv tool install punt-quarry
quarry install
quarry doctorcurl -fsSL https://raw.githubusercontent.com/punt-labs/quarry/6f90f11/install.sh -o install.sh
shasum -a 256 install.sh
cat install.sh
sh install.shRemote 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/6f90f11/install.sh | sh -s -- --networkGenerates 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/6f90f11/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.
Related MCP server: Local RAG
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 serveprocess loads the embedding model once and serves all Claude Code sessions via mcp-proxy over WebSocketPassive knowledge capture ---
quarry enablesets 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 searchNamed databases --- isolated LanceDB directories with independent sync registries. Switch with
usefor work/personal separationResearch agent ---
researchersubagent 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)
Command | What it does |
| Ingest a URL, directory, or file |
| Ingest inline text under a document name |
| Semantic search. Questions get synthesized answers; keywords get raw results |
| Search and synthesize an explanation |
| Find which document a claim comes from |
| Manage: |
MCP Tools
Tool | Purpose | Execution |
| Index a file or URL | Background |
| Index inline text | Background |
| Register directory for sync | Background |
| Re-index all registered directories | Background |
| Semantic search with filters | Sync |
| Document metadata or page text | Sync |
| Documents, collections, databases, registrations | Sync |
| Database statistics | Sync |
| Remove document or collection | Background |
| Remove registration (validates; errors if unknown) | Sync |
| Switch active database | Sync |
CLI
quarry ingest report.pdf # index a file
quarry ingest https://example.com # index a webpage
echo "notes" | quarry remember --name notes.md # index inline text
quarry find "revenue trends" # hybrid search (vector + FTS)
quarry list documents # list indexed documents
quarry register ~/Documents/notes # watch a directory
quarry sync # re-index registered dirs
quarry use work # switch database
quarry enable # set up project collections + captures
quarry disable # remove project registration + data
quarry captures init # bootstrap the private capture shadow repo
quarry captures push # re-scrub + push captures to the shadow
quarry status # database dashboard
quarry doctor # health check
quarry serve # start daemon on :8420
quarry install # set up daemon, TLS certs, mcp-proxy
# Remote connections
quarry login okinos.local --api-key <token> # TOFU login to remote server
quarry logout # disconnect, revert to local daemon
quarry remote list --ping # show remote config and health
# Agent memory tagging
quarry ingest notes.md --agent-handle claude --memory-type fact
quarry find "deployment steps" --agent-handle claude
echo "key insight" | quarry remember --name insight.md --agent-handle claude \
--memory-type observation --summary "Key insight from review"Setup
Quarry works with zero configuration. These environment variables are available for customization:
Variable | Default | Description |
| (auto) | ONNX execution provider: |
| (none) | Bearer token for |
|
| Base directory for all databases |
|
| Max characters per chunk (~450 tokens) |
|
| Overlap between consecutive chunks |
For the full configuration reference, see Architecture section 7.
Passive Knowledge Capture
Beyond explicit /ingest and /find commands, quarry runs as a Claude Code plugin with hooks that capture knowledge automatically during your sessions:
Hook | When it fires | What it does |
Session start | On every session start | Auto-registers your project directory and syncs it in the background. Your codebase is searchable without manual ingestion. |
Web fetch | After any | URLs Claude fetches during research are auto-ingested into the project's |
Pre-compact | Before context compaction | Captures the conversation transcript into the project's |
All hooks are fail-open — failures are ignored and never block Claude Code. Each hook is individually toggleable via .punt-labs/quarry/config.md YAML frontmatter. See AGENTS.md for the full integration model.
Privacy: captures are scrubbed before write
Captures (session transcripts and auto-ingested web fetches) are redacted at write time, before anything touches disk or the <name>-captures/web-captures collection. A single write choke point scrubs, in order, secrets → filesystem paths (/Users//home/<user>/ → ~/) → emails (→ [REDACTED:email]) → the local hostname (→ [REDACTED:hostname]) → profanity. Web-fetch captures also redact the source URL's userinfo, query, and fragment so a URL like …/reset?email=…&token=… cannot leak. Redaction is idempotent and fail-closed (on any scrub error, no capture is written). Deliberately-ingested content (quarry ingest, remember) is not scrubbed — only the automatic capture paths are, since those feed the shared/pushable collections. See DES-036.
Private capture shadow repo (<repo> → <repo>-quarry)
Redacted capture .md files live in the gitignored .punt-labs/quarry/captures/ dir with no durable home. Enable the optional shadow sync to push them to a per-project private repo <repo>-quarry instead. Opt in by uncommenting the shadow: block in .punt-labs/quarry/config.md:
shadow:
enabled: true # off by default — a network + security action
remote: "" # empty → derive <origin>-quarry from the public remote
acknowledge_unverified: false # required to push when gh cannot confirm the remote is privatePre-create the private repo first. quarry does not create it by default (a wrong owner or an accidental public repo would leak). Create <repo>-quarry as private and let the remote derive, or run quarry captures init --create to create it via gh (which verifies visibility is private before any push).
Once enabled, the captures dir becomes a standalone nested git repo. quarry captures push — and the tail of every quarry sync — re-scrubs the staged captures with the same DES-036 scrubber, aborts the commit if any file is not clean, then commits and pushes. Auth reuses your existing git credentials; quarry stores no new secret. The push is fail-open: a network or auth failure never blocks a session.
Visibility is load-bearing. The re-scrub cannot catch every residual (IDN emails, non-/Users//home paths, a hostname from another machine), so those are backstopped only by the remote being private. quarry therefore refuses to push to a verifiably public remote, and requires acknowledge_unverified: true in .punt-labs/quarry/config.md when gh is absent and it cannot confirm the remote is private. quarry doctor reports the shadow state, and flags a required failure if the public repo already tracks capture files (which git rm --cached stops going forward, but an already-pushed capture needs a history purge — git filter-repo/BFG + force-push — coordinated with the repo owner). See DES-039.
How It Works
Quarry runs as a daemon — one quarry serve process per machine holds the engine (embedding model, LanceDB, pipeline, sync registry). Claude Code sessions reach it through mcp-proxy over WebSocket:
stdio wss:// (TLS)
Claude Code <-----------------> mcp-proxy <---------------------> quarry serve
MCP JSON-RPC (~5 MB Go) pinned CA cert (one engine)One resident engine means the model loads once and MCP state is shared across sessions — no per-session ~200 MB reload. The mcp-proxy and remote connections use TLS with a self-signed, pinned CA — even on localhost.
The target is that every interface — CLI, library, and MCP — is a thin client of that one daemon over a versioned REST/WebSocket contract; this daemon-first model is specified in DES-031 v2 (ACCEPTED, in implementation). Today the CLI and library still load the engine in-process on local calls, and MCP can fall back to an in-process quarry mcp when mcp-proxy is absent; those local-engine paths are being removed.
quarry install downloads mcp-proxy (SHA256-verified, correct platform) and configures MCP clients.
Documentation
Architecture | Z Specification | Design | Agents | Changelog
Development
uv sync # install dependencies
make check # run all quality gates (lint, type, test)
make test # test suite only
make format # auto-format code
make docs # build LaTeX documents
make eval # retrieval-quality eval harness (MRR/success@k, dev/CI only)Roadmap
Direction tracks the PR/FAQ. Current focus:
Retrieval quality — a
make evalharness (per-bucket MRR/success@k + a metadata-pollution diagnostic) now baselines search on quarry's own data; embedding levers (contextual embeddings, late chunking) are measured against it before adoption. See docs/eval-harness-design.md.Private capture sync — captures redact PII at write time, and the opt-in per-project private shadow repo (
<repo>→<repo>-quarry, above) now pushes the redacted captures off the public repo entirely.
License
MIT
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/jmf-pobox/quarry'
If you have feedback or need assistance with the MCP directory API, please join our Discord server