# code-rag-mcp

> Use this tool when you need to efficiently search and explore large codebases using natural language queries. It solves problems of manual code searching, enabling developers to quickly find relevant code snippets and their source locations. The tool takes natural language queries as input and returns relevant code snippets with source locations, making it ideal for use cases such as code reuse, debugging, and knowledge sharing.

Canonical page: https://skillsregistry.net/skills/qduc-code-rag  
JSON: https://api.skillsregistry.net/v1/skills/qduc-code-rag

## Description

Enables semantic search over codebases using natural language queries, returning relevant code snippets with source locations. Integrates with Claude Code for automatic codebase exploration.

## Trust

- **Trust score (0–1):** 0.06
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/rfa2ljygz6)
- **Repository:** <https://github.com/qduc/code-rag>

## 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": "qduc-code-rag"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/qduc-code-rag` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/qduc-code-rag/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