# mu

> mu — 0ximu-mu. Use this tool when you need to analyze and understand complex codebases, as it provides AI assistants with deep insights through semantic graphs, BM25 search, and impact analysis. It solves problems related to code comprehension, review, and navigation, and accepts git repositories as input, generating actionable outputs for informed decision-making. Ideal for use cases involving large-scale code maintenance, optimization, and collaboration.

Canonical page: https://skillsregistry.net/skills/0ximu-mu  
JSON: https://api.skillsregistry.net/v1/skills/0ximu-mu

## Description

MCP server that gives AI assistants deep codebase understanding. Semantic graph, BM25 search, impact analysis, code review.

## Trust

- **Trust score (0–1):** 0.16
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/0ximu/mu)

## 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": "0ximu-mu"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/0ximu-mu` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/0ximu-mu/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