# League of Legends Mock Match Predictor

> Use this tool when you need to predict the outcome of a League of Legends match or compare the performance of different summoners. It solves problems such as informing team composition decisions and identifying areas for improvement by analyzing historical match data. The tool takes in summoner information and outputs predicted match outcomes and performance comparisons.

Canonical page: https://skillsregistry.net/skills/onepersonunicorn-lolgpt  
JSON: https://api.skillsregistry.net/v1/skills/onepersonunicorn-lolgpt

## Description

AI-powered League of Legends tool that simulates mock matches and compares summoners based on historical performance data.

## Trust

- **Trust score (0–1):** 0.91
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mgdc3ox7vp)
- **Repository:** <https://github.com/onepersonunicorn/lolgpt>

## 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": "onepersonunicorn-lolgpt"
    }
  }
}
```

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