Patronus AI MCP Server#1078
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olaservo
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| - <img height="12" width="12" src="https://avatars.githubusercontent.com/u/82347605?s=48&v=4" alt="OceanBase Logo" /> **[OceanBase](https://github.com/oceanbase/mcp-oceanbase)** - MCP Server for OceanBase database and its tools | ||
| - <img height="12" width="12" src="https://docs.octagonagents.com/logo.svg" alt="Octagon Logo" /> **[Octagon](https://github.com/OctagonAI/octagon-mcp-server)** - Deliver real-time investment research with extensive private and public market data. | ||
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| - <img height="12" width="12" src="https://www.patronus.ai/favicon-ico" alt="Patronus AI Logo" /> **[Patronus AI](https://github.com/patronus-ai/patronus-mcp-server)** - Test, evaluate, and optimize AI agents and RAG apps |
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For some reason this icon isn't rendering for me when I preview the rendered Readme with these changes, could you double check that this image is loading correctly?
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Thanks for your contribution to the servers list. This has been merged in this combined PR: #2075 This is a new process we're trying out, so if you see any issues feel free to re-open the PR and tag me. |
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Description
This PR adds the Patronus AI MCP Server to the official list of MCP implementations, linking to Patronus AI's repository. The update provides visibility for users who want to integrate Patronus AI's API for powerful LLM evaluation and optimization.
Server Details
• Server: Patronus AI MCP
• Changes to: README (added Patronus AI MCP Server to the list of available servers)
Motivation and Context
The Patronus AI MCP Server enables AI engineers to scalably and reliably test and optimize LLM systems like AI agents and RAG apps. It is challenging improve LLM system performance and reduce hallucinations and other unexpected behavior. To solve this problem, we developed evaluation models and optimization techniques that help companies ship higher quality AI products. This MCP Server provides an interface over the Patronus API, enabling anyone to ask questions and run evals without running any code at all. This democratizes the process of optimizing AI products within product teams.
How Has This Been Tested?
This change affects documentation only, so no functional testing was required. However, the Patronus AI MCP Server has been tested against a variety of functional and E2E tests (see repo), and it been validated for use with MCP-compatible clients.
Breaking Changes
No breaking changes.
Types of changes
Checklist
Additional context