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Patronus MCP Server

@patronus-ai

代码仓库

基本信息

分类

其他

许可证

Apache-2.0

传输方式

stdio

作者

patronus-ai

关于 Patronus MCP Server

暂无概览

#patronus#mcp-server#llm-optimization

Patronus MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "patronus-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

Patronus MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Patronus MCP Server?

An MCP server implementation for the Patronus SDK, providing a standardized interface for running LLM system optimizations, evaluations, and experiments.

How to use Patronus MCP Server?

Clone the repository, create a Python virtual environment, install dependencies with uv pip install -e ., then run the server with an API key via --api-key argument or the PATRONUS_API_KEY environment variable. Use the included test script for interactive evaluation or call the server’s tools through any MCP client.

Key features of Patronus MCP Server

  • Initialize Patronus with API key and project settings
  • Run single evaluations with configurable evaluators
  • Run batch evaluations with multiple evaluators
  • Run experiments with datasets
  • Create custom evaluator criteria in the Patronus API
  • List all available evaluators and their criteria
  • Custom evaluate using user-defined evaluator functions

Use cases of Patronus MCP Server

  • Evaluate LLM outputs for hallucinations or conciseness using remote evaluators
  • Run batch evaluations with multiple remote evaluators on the same input
  • Conduct experiments with a dataset and a mix of remote and custom evaluators
  • Create new evaluator criteria to match specific pass/fail conditions
  • Integrate custom evaluation logic via @evaluator decorated functions

常见问题

1

How do I supply the Patronus API key?

You can provide it either as a command‑line argument (`--api-key your_key`) or by setting the `PATRONUS_API_KEY` environment variable.

2

What runtime dependencies does the server require?

Python 3, a virtual environment, and the packages installed via `uv pip install -e .` and `uv pip install -e ".[dev]"` for development.

3

Does the server support custom evaluators?

Yes. You can define evaluator functions using the `@evaluator` decorator and pass them to the `custom_evaluate` tool, or configure a custom evaluator adapter for experiments.

4

How can I test the server interactively?

Run `python -m tests.test_live src/patronus_mcp/server.py` with an API key to get a menu of test options (single evaluation, batch evaluation). Results are shown as formatted JSON.

5

What transport or authentication does the server use?

The server uses the Model Context Protocol (MCP) and authenticates with the Patronus API via the provided API key. No other transport or auth method is documented.

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