io.github.norrietaylor/distillery-mcp

<p align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/norrietaylor/distillery/main/docs/assets/distillery-logo-dark-512.png" width="180"> <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/norrietaylor/distillery/main/docs/assets/distillery-logo-512.png" width="180"> <img alt="Distillery" src="https://raw.githubusercontent.com/norrietaylor/distillery/main/docs/assets/distillery-logo-512.png" width="180"> </picture> </p>

<h1 align="center">Distillery</h1>

<!-- mcp-name: io.github.norrietaylor/distillery-mcp -->

<p align="center"> <strong>Team Knowledge, Distilled</strong> <br> Capture, classify, connect, and surface team knowledge through conversational commands. </p>

<p align="center"> <a href="https://norrietaylor.github.io/distillery/">Documentation</a> · <a href="#skills">Skills</a> · <a href="#quick-start">Quick Start</a> · <a href="https://norrietaylor.github.io/distillery/roadmap/">Roadmap</a> · <a href="https://norrietaylor.github.io/distillery/presentation.html">Slides</a> </p>

<p align="center"> <a href="https://pypi.org/project/distillery-mcp/"><img src="https://img.shields.io/pypi/v/distillery-mcp" alt="PyPI version"></a> <a href="https://pypi.org/project/distillery-mcp/"><img src="https://img.shields.io/pypi/dm/distillery-mcp" alt="PyPI downloads"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/license-Apache%202.0-blue" alt="License"></a> <a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/python-3.11%2B-blue" alt="Python version"></a> </p>

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What is Distillery?

Distillery is a team knowledge base accessed through Claude Code skills. It refines raw information from working sessions, meetings, bookmarks, and conversations into concentrated, searchable knowledge — stored as vector embeddings in DuckDB and retrieved through natural language. Runs locally over stdio or as a hosted HTTP service with GitHub OAuth for team access.

Distillery captures the highest-value transformation — from noise to signal — and makes it a tool the whole team can use.

Full documentation: norrietaylor.github.io/distillery

<p align="center"> <img src="https://raw.githubusercontent.com/norrietaylor/distillery/main/docs/assets/distillery-demo.gif" alt="Distillery demo — /distill captures a decision, /pour synthesizes it" width="600"> </p>

Skills

Distillery provides 15 Claude Code slash commands:

Skill	Purpose	Example
/distill	Capture session knowledge with dedup detection	/distill "We decided to use DuckDB for local storage"
/recall	Semantic search with provenance	/recall distributed caching strategies
/pour	Multi-entry synthesis with citations	/pour how does our auth system work?
/compass	Contrast internal knowledge vs. ambient intelligence for a directional assessment	/compass our caching strategy
/bookmark	Store URLs with auto-generated summaries	/bookmark https://example.com/article #caching
/minutes	Meeting notes with append updates	/minutes --update standup-2026-03-22
/classify	Classify entries and triage review queue	/classify --inbox
/watch	Manage monitored feed sources	/watch add github:duckdb/duckdb
/radar	Ambient feed digest with source suggestions	/radar --days 7
/tune	Adjust feed relevance thresholds	/tune relevance 0.4
/digest	Team activity summary from internal entries	/digest --days 7 --project myapp
/gh-sync	Sync GitHub issues/PRs into the knowledge base	/gh-sync owner/repo --issues
/investigate	Deep context builder with relationship traversal	/investigate distributed caching
/briefing	Team knowledge dashboard with metrics	/briefing --days 7
/setup	Onboarding wizard for MCP connectivity and config	/setup

Quick Start

Step 1: Install the Plugin

claude plugin marketplace add norrietaylor/distillery
claude plugin install distillery

This installs all 15 skills. The plugin does not configure an MCP server automatically — run /setup (below) to add one. The recommended setup runs locally via uvx --from 'distillery-mcp[fastembed]>=0.6.0' distillery-mcp — a private, self-contained knowledge base on your machine, with on-device fastembed embeddings (no API key required). Requires Python 3.11+ and uv (install: curl -LsSf https://astral.sh/uv/install.sh | sh).

Step 2 (Optional): Use Jina or OpenAI Instead

The default fastembed provider runs offline with no API key. If you'd rather use a hosted embedding service, set DISTILLERY_EMBEDDING_PROVIDER and provide the matching API key:

# Jina (free tier at jina.ai)
export DISTILLERY_EMBEDDING_PROVIDER=jina
export JINA_API_KEY=jina_...

# Or OpenAI
export DISTILLERY_EMBEDDING_PROVIDER=openai
export OPENAI_API_KEY=sk-...

uvx inherits these from your shell environment. See distillery.yaml.example for the full provider configuration block (including Option C for fastembed model selection).

Restart Claude Code and run the onboarding wizard:

/setup

Try the Hosted Demo (Opt-In)

Want to evaluate without installing anything locally? Configure the hosted demo at distillery-mcp.fly.dev instead of a local server:

claude mcp add distillery --scope user --transport http --url https://distillery-mcp.fly.dev/mcp

Demo Server: distillery-mcp.fly.dev is for evaluation only. Do not store sensitive or confidential data.

See the Local Setup Guide for full configuration options, or deploy your own instance for team use.

Development

uv pip install -e ".[dev]"
# or
pip install -e ".[dev]"
pytest                              # run tests
mypy --strict src/distillery/       # type check
ruff check src/ tests/              # lint

See Contributing for the full guide.

License

Apache 2.0 — see LICENSE for details.