# Distill

> Use this tool when you need to organize and retain team knowledge across sessions, transforming raw input into actionable insights. Distill solves the problem of information loss and decision recall by providing a shared knowledge base, taking in raw data and outputting anonymous, factual information. It is ideal for teams requiring a collaborative and persistent memory of decisions and corrections.

Canonical page: https://skillsregistry.net/skills/5queezer-distill  
JSON: https://api.skillsregistry.net/v1/skills/5queezer-distill

## Description

MCP server that provides a shared team knowledge base by transforming raw input into anonymous, factual knowledge via a local LLM before storage, enabling cross-session recall of team decisions and corrections.

## Trust

- **Trust score (0–1):** 0.47
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/hljgm9i8si)
- **Repository:** <https://github.com/5queezer/distill>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "5queezer-distill"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/5queezer-distill` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/5queezer-distill/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt