Atla MCP Server
Atla MCP Server is a server implementation that provides a standardized interface for LLMs to interact with the Atla API for advanced LLM evaluation.
rating : 2.5 points
downloads : 21
What is Atla MCP Server?
Atla MCP Server is a standardized interface that allows language models to evaluate the quality of their responses through Atla's advanced evaluation models. It is based on the Model Context Protocol (MCP) and aims to simplify the performance evaluation of LLMs.How to use Atla MCP Server?
You can set up and connect to Atla MCP Server in just a few steps. You need an Atla API key, and then follow the guide to run the server and integrate it into your workflow.Applicable scenarios
Atla MCP Server is suitable for scenarios that require precise evaluation of responses generated by language models, such as dialogue systems, content generation tools, and the education field.Main features
Evaluate LLM responsesEvaluate the quality of LLM responses using specified evaluation criteria and return scores and detailed feedback.
Multi-criteria evaluationEvaluate LLM responses under multiple evaluation criteria simultaneously to provide more comprehensive feedback.
Advantages and limitations
Advantages
Supports multiple evaluation criteria to meet diverse needs.
Based on Atla's powerful evaluation models, the results are accurate and reliable.
Easy to integrate into existing workflows.
Open source and free to use, reducing development costs.
Limitations
Requires an Atla API key to run the server.
Processing very large datasets may require more computing resources.
Some advanced features may depend on specific environment configurations.
How to use Atla MCP Server
Install dependencies
Ensure that Python and the uv toolkit are installed to manage the server environment.
Start the server
Start Atla MCP Server via the command line and provide your API key.
Connect the client
Configure the MCP server address according to the tools you use (such as the OpenAI Agents SDK or Claude Desktop).
Usage examples
Evaluate response clarityTest whether the responses generated by the LLM are clear and easy to understand.
Multi-criteria evaluationComprehensively evaluate the performance of the LLM in multiple dimensions.
Frequently Asked Questions
How to obtain an Atla API key?
Can Atla MCP Server be run offline?
How to add custom evaluation criteria?
Related resources
Atla official website
Learn about Atla AI and its products.
Model Context Protocol
Learn how the MCP protocol works.
GitHub code repository
View the source code and contribute.
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