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Atla MCP Server

@spisupat

Repository

Basic information

Category

Other

Transports

stdio

Author

spisupat

About Atla MCP Server

Initial version of an mcp server for agents to interact with atla's models

#atla-mcp-server#mcp-server#llm-evaluation

Atla MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "atla-mcp-server": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Atla MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Atla MCP Server?

An MCP server implementation that provides a standardized interface for LLMs to interact with the Atla SDK, enabling access to state-of-the-art evaluation models like Selene 1. It is intended for developers building AI agents that need automated quality evaluation of responses.

How to use Atla MCP Server?

Install the server by cloning the repository, installing dependencies with uv venv and uv sync, and setting the ATLA_API_KEY environment variable. Then configure it as an MCP server in OpenAI Agents SDK, Claude Desktop, or Cursor using the provided JSON configurations.

Key features of Atla MCP Server

  • Evaluate individual responses using Selene 1.
  • Run batch evaluations with Selene 1.
  • List available evaluation metrics.
  • Create new evaluation metrics.
  • Fetch metrics by name.

Use cases of Atla MCP Server

  • Automatically evaluate and improve LLM responses during agent execution.
  • Perform iterative refinement by evaluating responses for cliché or helpfulness.
  • Integrate standardized evaluation into multi-agent workflows.

Frequently asked questions

1

What is Atla MCP Server used for?

It provides a standardized interface for LLMs to evaluate responses using Atla’s evaluation models, such as Selene 1.

2

What dependencies are required?

You need Python, `uv` installed on your system, and an `ATLA_API_KEY`. For OpenAI Agents integration, you also need the `OPENAI_API_KEY` environment variable.

3

Where does the API key come from?

Your `ATLA_API_KEY` can be obtained from your Atla account at https://www.atla-ai.com/sign-in.

4

How does the server communicate?

The server uses the stdio transport protocol, configured as a local MCP server via command-line execution.

5

What integrations are supported?

Atla MCP Server can be used with OpenAI Agents SDK, Claude Desktop, and Cursor MCP clients.

Comments

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