# mcp-knowledge-graph

> Use this tool when you need to manage and visualize complex relationships between entities, solving problems of data integration and discovery. It takes in unstructured data from sources like Git repositories and outputs a navigable graph of interconnected concepts. Ideal for use cases involving knowledge management, data mining, and information retrieval, where insights from large datasets are crucial.

Canonical page: https://skillsregistry.net/skills/itseasy21-mcp-knowledge-graph  
JSON: https://api.skillsregistry.net/v1/skills/itseasy21-mcp-knowledge-graph

## Trust

- **Trust score (0–1):** 0.92
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/itseasy21/mcp-knowledge-graph)
- **Repository:** <https://github.com/itseasy21/mcp-knowledge-graph>

## 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": "itseasy21-mcp-knowledge-graph"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/itseasy21-mcp-knowledge-graph` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/itseasy21-mcp-knowledge-graph/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