# rag-mcp

> rag-mcp — jaimenbell-rag-mcp. Use this tool when you need to retrieve relevant information from a corpus based on a given query, leveraging local embeddings to return cited chunks of knowledge. It solves problems related to information retrieval, question answering, and text search, providing a minimal yet effective solution. Ideal for use cases where precise and context-specific knowledge retrieval is required, such as research, data analysis, or content creation.

Canonical page: https://skillsregistry.net/skills/jaimenbell-rag-mcp  
JSON: https://api.skillsregistry.net/v1/skills/jaimenbell-rag-mcp

## Description

Minimal RAG-over-a-corpus MCP retrieval: search_knowledge returns cited chunks. Local embeddings.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ksr79asxat)
- **Repository:** <https://github.com/jaimenbell/rag-mcp>

## 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": "jaimenbell-rag-mcp"
    }
  }
}
```

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