Continuously capture, search, and synthesize project knowledge from working sessions, meetings, bookmarks, and GitHub issues into a searchable knowledge base with structured retrieval, contradiction detection, and gap analysis
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.
Distillery provides 14 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?
/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 14 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_...
