# Atla

> Use this tool when you need to evaluate the quality of large language model (LLM) responses against multiple criteria. Atla MCP Server provides a standardized interface for assessing response quality, returning numerical scores and textual critiques, and supports various connection methods for seamless integration with different MCP clients. It solves problems in LLM evaluation, offering a robust solution for AI assistants to leverage state-of-the-art evaluation models.

Canonical page: https://skillsregistry.net/skills/atla  
JSON: https://api.skillsregistry.net/v1/skills/atla

## Description

Atla MCP Server provides a standardized interface for LLMs to interact with the Atla API for state-of-the-art LLMJ evaluation. It offers tools for evaluating LLM responses against single or multiple criteria, returning both numerical scores and textual critiques. Built with Python 3.11 and distributed under the MIT license, this server enables AI assistants to leverage Atla's evaluation models for assessing response quality across various dimensions. The implementation supports multiple connection methods including OpenAI Agents SDK, Claude Desktop, and Cursor, making it accessible for developers working with different MCP clients.

## Trust

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

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/atla)
- **Repository:** <https://github.com/atla-ai/atla-mcp-server>

## 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": "atla"
    }
  }
}
```

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