Interactive Feedback MCP server

This MCP server provides an interactive feedback mechanism for AI assistants, ensuring they check with users before completing tasks. It helps reduce premium API calls by consolidating multiple potential tool calls into a single feedback-aware request.

Installation

Prerequisites

• Python 3.11 or newer
• uv (Python package manager)

Install uv with:

# Windows
pip install uv

# Linux/Mac
curl -LsSf https://astral.sh/uv/install.sh | sh

Setup Process

1. Get the code:

git clone https://github.com/noopstudios/interactive-feedback-mcp.git

2. Navigate to the directory:

cd interactive-feedback-mcp

3. Install dependencies:

uv sync

4. Run the MCP Server:

uv run server.py

Cursor Configuration

You'll need to configure Cursor to use this custom MCP server. This can be done via a mcp.json configuration file:

{
  "mcpServers": {
    "interactive-feedback-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/interactive-feedback-mcp",
        "run",
        "server.py"
      ],
      "timeout": 600,
      "autoApprove": [
        "interactive_feedback"
      ]
    }
  }
}

Important: Replace /path/to/interactive-feedback-mcp with the actual path where you cloned the repository.

Usage

Prompt Engineering

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

Whenever you want to ask a question, always call the MCP interactive_feedback.
Whenever you're about to complete a user request, call the MCP interactive_feedback instead of simply ending the process.
Keep calling MCP until the user's feedback is empty, then end the request.

Using the Tool

The AI assistant will call the interactive_feedback tool like this:

<use_mcp_tool>
  <server_name>interactive-feedback-mcp</server_name>
  <tool_name>interactive_feedback</tool_name>
  <arguments>
    {
      "project_directory": "/path/to/your/project",
      "summary": "I've implemented the changes you requested and refactored the main module."
    }
  </arguments>
</use_mcp_tool>

Configuration Options

The MCP server uses Qt's QSettings to store configuration on a per-project basis:

• Command to run
• Auto-execution on next startup
• Visibility state of command section
• Window geometry and state

Settings are saved in platform-specific locations under organization "FabioFerreira" and application "InteractiveFeedbackMCP".

Testing Mode

To run the server in a testing mode with a web interface:

uv run fastmcp dev server.py

This opens a web interface for interacting with the MCP tools during testing.

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "interactive-feedback-mcp" '{"command":"uv","args":["--directory","/Users/fabioferreira/Dev/scripts/interactive-feedback-mcp","run","server.py"],"timeout":600,"autoApprove":["interactive_feedback"]}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "interactive-feedback-mcp": {
            "command": "uv",
            "args": [
                "--directory",
                "/Users/fabioferreira/Dev/scripts/interactive-feedback-mcp",
                "run",
                "server.py"
            ],
            "timeout": 600,
            "autoApprove": [
                "interactive_feedback"
            ]
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this to your configuration file:

{
    "mcpServers": {
        "interactive-feedback-mcp": {
            "command": "uv",
            "args": [
                "--directory",
                "/Users/fabioferreira/Dev/scripts/interactive-feedback-mcp",
                "run",
                "server.py"
            ],
            "timeout": 600,
            "autoApprove": [
                "interactive_feedback"
            ]
        }
    }
}

3. Restart Claude Desktop for the changes to take effect