Distillery MCP Server
io.github.norrietaylor/distillery-mcp
Team knowledge base with semantic search, feed intelligence, and Claude Code integration.
What is the Distillery MCP server?
Distillery is a team knowledge base MCP server that captures, classifies, and surfaces organizational knowledge through conversational slash commands. It stores information as vector embeddings in DuckDB and retrieves it via natural language search, running locally or as a hosted service with GitHub OAuth for team access.
Distillery helps teams distill raw information from sessions, meetings, bookmarks, and conversations into searchable, connected knowledge. It provides 15 Claude Code skills for capturing decisions, synthesizing insights, monitoring feeds, syncing GitHub issues, and generating team activity summaries—all accessible through natural language queries.
How to install Distillery
Copy-paste configuration for popular MCP clients.
JINA_API_KEYsecretAPI key for Jina embedding provider
OPENAI_API_KEYsecretAPI key for OpenAI embedding provider (alternative to Jina)
Tools & capabilities
Tools this server exposes to the agent.
/distill— Capture session knowledge with deduplication detection/recall— Semantic search with provenance tracking/pour— Multi-entry synthesis with citations/compass— Contrast internal knowledge vs. ambient intelligence for directional assessment/bookmark— Store URLs with auto-generated summaries/minutes— Meeting notes with append updates/classify— Classify entries and triage review queue/watch— Manage monitored feed sources/radar— Ambient feed digest with source suggestions/tune— Adjust feed relevance thresholds/digest— Team activity summary from internal entries/gh-sync— Sync GitHub issues and pull requests into the knowledge base/investigate— Deep context builder with relationship traversal/briefing— Team knowledge dashboard with metrics/setup— Onboarding wizard for MCP connectivity and configuration
Use cases
- Capture and retrieve team decisions and architectural choices through semantic search
- Synthesize multi-source knowledge into coherent answers with citations
- Monitor GitHub repositories and external feeds for relevant updates
- Generate team activity summaries and knowledge dashboards for project visibility
- Build contextual understanding of systems by traversing related knowledge entries
Distillery MCP server FAQ
Distillery is a team knowledge base that captures information from sessions, meetings, and feeds, stores it as searchable vector embeddings, and surfaces it through 15 Claude Code slash commands for semantic search, synthesis, and team intelligence.
Yes. The default setup uses fastembed for local, offline embeddings with no API key required. Optional integrations with Jina or OpenAI are available if you prefer hosted embedding services.
Run `claude plugin marketplace add norrietaylor/distillery` and `claude plugin install distillery`, then execute `/setup` to configure the MCP server. The recommended setup runs locally via `uvx --from 'distillery-mcp[fastembed]>=0.6.0' distillery-mcp` (requires Python 3.11+ and uv).
Local setups require no authentication. The optional hosted version supports GitHub OAuth for team access. A public demo is available at distillery-mcp.fly.dev for evaluation.
Distillery stores vector embeddings, meeting notes, bookmarks, GitHub synced issues/PRs, and team knowledge entries in a local DuckDB database. Hosted deployments can be self-managed for privacy.
Yes. The `/gh-sync` command syncs GitHub issues and pull requests into your knowledge base for searchable integration with team knowledge.
README (reference)
Source of truth, from the repository.
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.
<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>Full documentation: norrietaylor.github.io/distillery
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.devis 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.
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