# Repository to LLM Context

> Use this tool when you need to convert traditional code repositories into formats compatible with large language models (LLMs). It solves the problem of bridging the gap between legacy code bases and modern AI language models, enabling seamless integration and analysis. The tool takes code repositories as input and outputs LLM-friendly formats, making it ideal for use cases where AI-driven code understanding and generation are required.

Canonical page: https://skillsregistry.net/skills/crisschan-repo2llm  
JSON: https://api.skillsregistry.net/v1/skills/crisschan-repo2llm

## Description

mcp-repo2llm is a MCP server that transforms code repositories into LLM-friendly formats. A powerful tool that transforms code repositories into LLM-friendly formats, bridging the gap between traditional code bases and modern AI language models. This repo is based on RepoToTextForLLMs, which provides core functionality for converting repositories into LLM-readable formats.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/crisschan-repo2llm)
- **Repository:** <https://github.com/crisschan/mcp-repo2llm>

## 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": "crisschan-repo2llm"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/crisschan-repo2llm` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/crisschan-repo2llm/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