# rag-reference-discovery-mcp

> rag-reference-discovery-mcp — flatmarstheory-rag-reference-discovery-mcp. Use this tool when you need to discover and validate scholarly metadata from text extracted by an attachment/RAG system, solving problems of data accuracy and consistency in research and academic contexts. It provides a read-only MCP server for independent validation, taking in text extracts as input and outputting validated metadata. Ideal for use cases requiring reliable scholarly data, such as research paper analysis or citation management.

Canonical page: https://skillsregistry.net/skills/flatmarstheory-rag-reference-discovery-mcp  
JSON: https://api.skillsregistry.net/v1/skills/flatmarstheory-rag-reference-discovery-mcp

## Description

A production-oriented, read-only MCP server for discovering and independently validating scholarly metadata from text extracted by an MCP client's own attachment/RAG system.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/flatmarstheory/rag-reference-discovery-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": "flatmarstheory-rag-reference-discovery-mcp"
    }
  }
}
```

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

---
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