# metricmate-mcp

> metricmate-mcp — marilynceo-metricmate-mcp. Use this tool when you need to evaluate and quantify the quality of Large Language Model (LLM) responses, solving problems related to relevance, accuracy, tone, and consistency. It provides outputs such as hallucination scoring and consistency checks, taking LLM response inputs through a git interface. This tool is ideal for tracking and improving LLM output quality in various applications.

Canonical page: https://skillsregistry.net/skills/marilynceo-metricmate-mcp  
JSON: https://api.skillsregistry.net/v1/skills/marilynceo-metricmate-mcp

## Description

LLM Output Quality Evaluation u2014 quantify, evaluate, and track LLM response quality: relevance, accuracy, tone, hallucination scoring, and consistency checks

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/marilynceo/metricmate-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": "marilynceo-metricmate-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/marilynceo-metricmate-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/marilynceo-metricmate-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