# Knowledge Graph Server

> Use this tool when you need to manage and analyze complex knowledge graphs, integrating seamlessly with AI assistants to query and manipulate data. It solves problems related to knowledge workflow management, data visualization, and version control, accepting graph data as input and producing visualizations and query results as output. Ideal for use cases involving topology, timeline, and ontology analysis, particularly when integrating with MCP-compatible AI assistants.

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

## Description

Manage, analyze, and visualize knowledge graphs with support for multiple graph types including topologies, timelines, and ontologies. Seamlessly integrate with MCP-compatible AI assistants to query and manipulate knowledge graph data. Benefit from comprehensive resource management and version status tracking to enhance your knowledge workflows.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-04-27

## Source

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

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

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