mcpField
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User Feedback MCP

User Feedback MCP

Local
github.com/mrexodiaAI & Agents54Updated 83w ago
Repository

About User Feedback MCP

User Feedback MCP is a simple MCP server that enables a human-in-the-loop workflow in tools such as Cline and Cursor. It is useful when developing desktop applications that need complex user interaction testing.

Key features

  1. 01Provides a user_feedback tool for requesting feedback
  2. 02Loads optional .user-feedback.json configuration
  3. 03Can run a project command automatically on startup
  4. 04Runs through uv with a simple setup

Use cases

  1. 01Asking the user for confirmation before Cline completes a task
  2. 02Testing desktop applications that need complex user interaction
  3. 03Collecting human feedback during development in Cursor

MCP support

This project is an MCP server that exposes a user_feedback tool to MCP clients so they can request and receive user feedback.

#mcp#cursor#cline#mcp-server#modelcontextprotocol

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

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:

{
  "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:
{
  "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

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

<use_mcp_tool>
<server_name>github.com/mrexodia/user-feedback-mcp</server_name>
<tool_name>user_feedback</tool_name>
<arguments>
{
  "project_directory": "C:/MCP/user-feedback-mcp",
  "summary": "I've implemented the changes you requested."
}
</arguments>
</use_mcp_tool>

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.