# Eval_MCP

> Eval_MCP — ayushsaha184-eval-mcp. Use this tool when you need to evaluate and improve the accuracy of RAG-based systems, and leverage 15 specialized tools to identify and address performance issues. It solves problems related to model accuracy and reliability, providing actionable insights through various evaluation metrics as output. Ideal for use cases where RAG system optimization is crucial, with input support for git integration.

Canonical page: https://skillsregistry.net/skills/ayushsaha184-eval-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ayushsaha184-eval-mcp

## Description

An MCP server that offers 15 specialized tools to evaluate and improve the accuracy of RAG based systems.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/AyushSaha184/Eval_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": "ayushsaha184-eval-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ayushsaha184-eval-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ayushsaha184-eval-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