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Servers/Code Execution/Atla
Code ExecutionOfficial
A

Atla

Enable AI agents to interact with the Atla API for state-of-the-art LLMJ evaluation.

17 starsUpdated Jul 21, 2025
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Overview

> [!CAUTION] > This repository was archived on July 21, 2025. The Atla API is no longer active. An MCP server implementation providing a standardized interface for LLMs to interact with the Atla API for state-of-the-art LLMJ evaluation. > Learn more about Atla here. Learn more about the Model Context Protocol here. - evaluate_llm_response: Evaluate an LLM's response to a prompt using a given evaluation criteria. This function uses an Atla evaluation model under the hood to return a dictionary containing a score for the model's response and a textual critique containing feedback on the model's response. - evaluate_llm_response_on_multiple_criteria: Evaluate an LLM's response to a prompt across _multiple_ evaluation criteria. This function uses an Atla evaluation model under the hood to return a list of dictionaries, each containing an evaluation score and critique for a given criteria.

Installation

pip install openai-agents

Configuration

{
  "mcpServers": {
    "atla-mcp-server": {
      "command": "uvx",
      "args": ["atla-mcp-server"],
      "env": {
        "ATLA_API_KEY": "<your-atla-api-key>"
      }
    }

Capabilities

  • Evaluate a single LLM response

    Score and critique an LLM's answer against a custom evaluation criterion using `evaluate_llm_response`.

  • Evaluate across multiple criteria

    Assess an LLM response on several criteria at once and get per-criterion scores and feedback with `evaluate_llm_response_on_multiple_criteria`.

Tags

  • development

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