# GraphRAG MCP

> Use this tool when you need to efficiently retrieve and extract specific information from large sets of enterprise documents. GraphRAG MCP solves the problem of scattered and unstructured data by utilizing graph-based reasoning and knowledge graphs to identify and connect relevant entities and relationships. It takes in unstructured document data and outputs structured information, making it ideal for use cases requiring accurate and rapid document analysis.

Canonical page: https://skillsregistry.net/skills/embracefailure-mcphub  
JSON: https://api.skillsregistry.net/v1/skills/embracefailure-mcphub

## Description

Enables enterprise document retrieval using graph-based reasoning and knowledge graphs. Allows agents to search and extract information from scattered documents through structured entity and relationship extraction.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-22

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/uyqnpqsoez)
- **Repository:** <https://github.com/embracefailure/MCPHub>

## 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": "embracefailure-mcphub"
    }
  }
}
```

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