What does the .user-feedback.json file do?

It configures the command to run and whether it should execute automatically on startup.

How do I install this MCP server in Cline?

Install 'uv', clone the repo, then configure Cline's MCP servers with the provided JSON snippet pointing to the server.py script.

Can I test the MCP server locally?

Yes, run 'uv run fastmcp dev server.py' to open a web interface at http://localhost:5173 for testing.

User Feedback MCP

developer-toolshuman-in-the-loopfeedbackclinecursor

MCP server enabling human-in-the-loop workflows for developer tools like Cline and Cursor.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "mrexodia-user-feedback-mcp": {
      "command": "uvx",
      "args": [
        "uv"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

This MCP server facilitates human-in-the-loop interactions by requesting user feedback during task execution in compatible AI tools. It is useful for desktop app development requiring complex user interactions and testing. The server supports configuration via a .user-feedback.json file to automate command execution and integrates with clients like Cline.

Use cases

Request user feedback before task completion

Automate command execution with user confirmation

Test complex user interactions in desktop apps

Integrate human feedback loops in AI workflows

Key features

Human-in-the-loop feedback tool

Configurable automatic command execution

Supports .user-feedback.json project config

Web interface for local testing

Integration instructions for Cline MCP

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by User Feedback MCP.

Extracted Tool Capabilities

Human-in-the-loop feedback tool

Configurable automatic command execution

Supports .user-feedback.json project config

Web interface for local testing

Integration instructions for Cline MCP

Documentation Overview

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:

config.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

Install uv globally:
- Windows: pip install uv
- Linux/Mac: curl -LsSf https://astral.sh/uv/install.sh | sh
Clone this repository, for this example C:\MCP\user-feedback-mcp.
Navigate to the Cline MCP Servers configuration (see screenshot).
Click on the Installed tab.
Click on Configure MCP Servers, which will open cline_mcp_settings.json.
Add the user-feedback-mcp server:

config.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

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

<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>

Read the full README →View source on GitHub →

Related MCP Servers

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

npm downloads

37k

Package downloads in the last 30 days.

Last commit

1y ago

Most recent push to the default branch.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about User Feedback MCP

Add 'Before completing the task, use the user_feedback MCP tool to ask the user for feedback.' to your custom prompt.

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Technical Specs & Signals

CategoryDeveloper Tools

PricingFree

10/10 checks healthy over the last 30d

45Quality signal: Fair · 45/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools17/30

Adoption & activity7/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 3Low 4

Scanned 22d ago via OSV.dev · uv (PyPI)

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Overview

Use cases

Request user feedback before task completion

Automate command execution with user confirmation

Test complex user interactions in desktop apps

Integrate human feedback loops in AI workflows

Key features

Human-in-the-loop feedback tool

Configurable automatic command execution

Supports .user-feedback.json project config

Web interface for local testing

Integration instructions for Cline MCP

Documentation Overview

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:

config.json

{

  "command": "npm run dev",

  "execute_automatically": false

}

Installation (Cline)

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

Screenshot showing installation steps

Install uv globally:
- Windows: pip install uv
- Linux/Mac: curl -LsSf https://astral.sh/uv/install.sh | sh
Clone this repository, for this example C:\MCP\user-feedback-mcp.
Navigate to the Cline MCP Servers configuration (see screenshot).
Click on the Installed tab.
Click on Configure MCP Servers, which will open cline_mcp_settings.json.
Add the user-feedback-mcp server:

config.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

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

<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>

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

npm downloads

37k

Package downloads in the last 30 days.

Last commit

1y ago

Most recent push to the default branch.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.