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Privacy-first team memory MCP server — local LLM distillation before team sync

Project description

🧪 Distill

CI Python 3.11+ License: MIT

An MCP server that gives Claude Code a shared team knowledge base — a local LLM transforms your raw input into anonymous, factual knowledge before anything leaves your device.

No author. No frustration. No names. Just a clean, reusable fact.

Distill demo — raw thought to clean team fact

Raw input → local Ollama → review → team DB or discard

Quick Start

pip install distill-mcp
ollama pull gemma3:4b && ollama pull nomic-embed-text
claude mcp add distill -- python -m distill_mcp

Then in Claude Code:

You:    "No, we don't use REST here. We switched to gRPC last month."

Claude: [saves to distill]
        Got it. I've noted that the team uses gRPC, not REST.

        ... next session, different repo ...

You:    "Set up the API for this new service."

Claude: [searches distill → finds gRPC decision]
        Based on your team's knowledge, I'll set up a gRPC
        service since the team switched from REST last month.

Distill saves when you correct a mistake or make a decision, and searches before proposing architecture — no prompting needed.

What makes this different

Every "memory MCP" stores your raw text in a database. Distill doesn't. The local LLM is a mandatory privacy gateway that transforms personal thoughts into impersonal team knowledge.

Raw stays local LLM distills Team sync Platform agnostic
Claude-Mem Partial (<private> opt-out) Cloud API compresses Single-user Claude Code only
Cipher No No Yes No
Supermemory No No Yes No
Mem0 Yes No No Yes
Memctl Yes No Yes Yes
Distill Yes Yes Yes Yes

Based on public documentation as of March 2026.

Documentation

Development

git clone https://github.com/5queezer/distill.git
cd distill
uv sync
uv run pytest tests/ -x -v

License

MIT

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