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MLflow Prompt Registry MCP Server

by B-Step62
GitHub
TypeScript
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Integrations

  • Connects to MLflow Prompt Registry, allowing access to managed prompt templates through MCP, with tools for listing available prompts and retrieving specific prompts with variable arguments.

MLflow 提示注册表 MCP 服务器

MLflow Prompt Registry的模型上下文协议 (MCP) 服务器，支持访问 MLflow 中管理的提示模板。

此服务器实现了MCP Prompts 规范，用于发现和使用来自 MLflow Prompt Registry 的提示模板。其主要用例是在 Claude Desktop 中加载来自 MLflow 的提示模板，以便用户方便地指导 Claude 执行重复性任务或常见工作流程。

工具

  • list-prompts
    • 列出可用的提示
    • 输入：
      • cursor （可选字符串）：分页光标
      • filter （可选字符串）：过滤提示
    • 返回：提示对象列表
  • get-prompt
    • 检索并编译特定提示
    • 输入：
      • name （字符串）：要检索的提示的名称
      • arguments （可选对象）：带有提示变量的 JSON 对象
    • 返回：编译后的提示对象

设置

1：安装MLflow并启动提示注册表

如果您尚未托管 Prompt Registry，请安装并启动 MLflow 服务器：

pip install mlflow>=2.21.1 mlflow server --port 5000

2：在 MLflow 中创建提示模板

如果您还没有，请按照本指南在 MLflow 中创建提示模板。

3：搭建 MCP 服务器

npm install npm run build

4：将服务器添加到Claude Desktop

通过编辑claude_desktop_config.json配置 Claude for Desktop：

{ "mcpServers": { "mlflow": { "command": "node", "args": ["<absolute-path-to-this-repository>/dist/index.js"], "env": { "MLFLOW_TRACKING_URI": "http://localhost:5000" } } } }

确保将MLFLOW_TRACKING_URI替换为您的实际 MLflow 服务器地址。

This server cannot be installed

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通过 Claude Desktop 访问 MLflow 中管理的提示模板，允许用户使用保存的模板指导 Claude 执行重复性任务或常见工作流程。

  1. Tools
    1. Setup
      1. 1: Install MLflow and Start Prompt Registry
      2. 2: Create a prompt template in MLflow
      3. 3: Build MCP Server
      4. 4: Add the server to Claude Desktop

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