Whenever you're about to complete a user request, call the MCP instead of simply ending the process. Keep calling MCP until the user's feedback is
MCP Feedback Collector connects MCP Feedback Collector to AI assistants that speak the Model Context Protocol. Whenever you're about to complete a user request, call the MCP instead of simply ending the process. Keep calling MCP until the user's feedback is empty, then end the request. mcp-feedback-collector.collect_feedback ".
Whenever you're about to complete a user request, call the MCP instead of simply ending the process. Keep calling MCP until the user's feedback is empty, then end the request. mcp-feedback-collector.collect_feedback "
Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
{
"mcpServers": {
"feedback-collector": {
"command": "uvx",
"args": ["uvx"],
"env": {
"PYTHONIOENCODING": "your-value",
"MCP_DIALOG_TIMEOUT": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| PYTHONIOENCODING | Configuration value read at startup. | Optional |
| MCP_DIALOG_TIMEOUT | Configuration value read at startup. | Optional |
Read, search and edit files inside allowed directories with the Model Context Protocol reference Filesystem server.
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🧙🏻 Integrated TinyPNG MCP server, quickly use TinyPNG through LLMs.
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Trace code history, commit reasoning, and PR context directly from Git logs.