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    User Feedback Mcp

    Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor.

    49 stars
    Python
    Updated Oct 31, 2025
    cline
    cursor
    mcp
    mcp-server
    modelcontextprotocol

    Table of Contents

    • Prompt Engineering
    • .user-feedback.json
    • Installation (Cline)
    • Development
    • Available tools

    Table of Contents

    • Prompt Engineering
    • .user-feedback.json
    • Installation (Cline)
    • Development
    • Available tools

    Documentation

    User Feedback MCP

    Simple MCP Server to enable a human-in-the-loop workflow in tools like Cline and Cursor. This is especially useful for developing desktop applications that require complex user interactions to test.

    Screenshot showing the feedback UI

    Prompt Engineering

    For the best results, add the following to your custom prompt:

    Before completing the task, use the user_feedback MCP tool to ask the user for feedback.

    This will ensure Cline uses this MCP server to request user feedback before marking the task as completed.

    .user-feedback.json

    Hitting _Save Configuration_ creates a .user-feedback.json file in your project directory that looks like this:

    json
    {
      "command": "npm run dev",
      "execute_automatically": false
    }

    This configuration will be loaded on startup and if execute_automatically is enabled your command will be instantly executed (you will not have to click _Run_ manually). For multi-step commands you should use something like Task.

    Installation (Cline)

    To install the MCP server in Cline, follow these steps (see screenshot):

    Screenshot showing installation steps

    1. Install uv globally:

    • Windows: pip install uv
    • Linux/Mac: curl -LsSf https://astral.sh/uv/install.sh | sh

    2. Clone this repository, for this example C:\MCP\user-feedback-mcp.

    3. Navigate to the Cline _MCP Servers_ configuration (see screenshot).

    4. Click on the _Installed_ tab.

    5. Click on _Configure MCP Servers_, which will open cline_mcp_settings.json.

    6. Add the user-feedback-mcp server:

    json
    {
      "mcpServers": {
        "github.com/mrexodia/user-feedback-mcp": {
          "command": "uv",
          "args": [
            "--directory",
            "c:\\MCP\\user-feedback-mcp",
            "run",
            "server.py"
          ],
          "timeout": 600,
          "autoApprove": [
            "user_feedback"
          ]
        }
      }
    }

    Development

    sh
    uv run fastmcp dev server.py

    This will open a web interface at http://localhost:5173 and allow you to interact with the MCP tools for testing.

    Available tools

    code
    github.com/mrexodia/user-feedback-mcp
    user_feedback
    
    {
      "project_directory": "C:/MCP/user-feedback-mcp",
      "summary": "I've implemented the changes you requested."
    }

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