minidoracat/mcp-feedback-enhanced

Enhanced MCP server for interactive user feedback and command execution in AI-assisted development, featuring dual interface support (Web UI and Desktop...

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Summary Information

Updated 39 minutes ago
Added to GitGenius on September 18th, 2026
Created on May 29th, 2025
Open Issues & Pull Requests: 8 (+0)
GitHub issues: Enabled
Number of forks: 349
Total Stargazers: 3,766 (+0)
Total Subscribers: 21 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 15.6 hours
Mean response time: 60.8 days
90th percentile: 370.3 days
Tracked items: 188

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Issue Activity (beta)

Open issues: 8
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 333 days
Stale 30+ days: 2
Stale 90+ days: 2

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (24)
  • enhancement (15)
  • configuration (13)
  • gui (12)
  • web (11)
  • question (9)
  • superseded (7)
  • v2-wontfix (7)

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Detailed Description

MCP Feedback Enhanced is an MCP server that enables interactive user feedback and command execution within AI-assisted development workflows, offering both Web UI and Desktop Application interfaces with automatic environment detection.

The tool addresses the need to insert human checkpoints into long-running AI tasks by providing a bidirectional communication channel between an AI assistant and a user. It works by exposing feedback collection endpoints through the Model Context Protocol, allowing an AI system to pause execution, present information to a user through either a web interface or desktop application, and wait for user input before proceeding. The server handles environment detection automatically, routing requests to the appropriate interface based on what is available in the user's setup.

Developers should adopt this tool if they are building AI-assisted workflows where human validation or decision-making is required at specific points in task execution. It suits projects using Claude or other MCP-compatible AI clients where pausing for user confirmation would improve reliability or safety. The original motivation of consolidating multiple round-trips to save API quota no longer applies given changes in pricing models, so the tool is now positioned as a mechanism for inserting human oversight into automated processes. If your AI client natively supports Elicitation or MCP Apps for interactive UI, those built-in capabilities may cover your needs without requiring this server.

The project maintains focus on security and compatibility. Recent work addressed a command execution vulnerability where unauthenticated WebSocket connections could run arbitrary programs, and fixed Cross-Site WebSocket Hijacking by validating request origins before accepting connections. The tool was updated to resolve breaking changes in upstream dependencies that rendered installations unusable, and image serialization was corrected to use standard MCP types.