Atla
Enable AI agents to interact with the Atla API for state-of-the-art LLMJ evaluation.
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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 The Atla API is no longer active.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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