User Feedback MCP
Enable a human-in-the-loop feedback workflow in AI coding tools.
Installation
Les étapes d'installation sont dans la documentation ci-dessous. Documentation
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
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.
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):
- Install uv globally:
- Windows:
pip install uv - Linux/Mac:
curl -LsSf https://astral.sh/uv/install.sh | sh
- Windows:
- 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-mcpserver:
{
"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>
Questions fréquentes
Qu'est-ce que User Feedback MCP ?
Enable a human-in-the-loop feedback workflow in AI coding tools.
Comment installer User Feedback MCP ?
Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.
User Feedback MCP est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient User Feedback MCP ?
Il est publié par mrexodia. AI.tn le référence sans le maintenir ni le recommander.
Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.