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• Interactive Feedback MCP

  harrylee47

  A

  license

  -Not graded

  quality

  C

  maintenance

  Enables AI-assisted development tools like Cursor, Cline, and Windsurf to request user confirmation before acting, running shell commands and displaying their output inside a Qt feedback window that returns user notes and logs to the model. This human-in-the-loop loop lets the assistant consolidate many speculative tool calls into a single feedback-aware request, saving API usage and improving accuracy.

  Updated 21 days ago (2026-10-02 12:54 UTC)

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• ai-intervention-agent

  fastmcp-me

  A

  license

  -Not graded

  quality

  D

  maintenance

  Enables real-time user intervention for MCP agents via a Web UI and interactive_feedback tool, allowing users to review context and send instructions when agents drift from intent.

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• MCP Feedback Enhanced

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  F

  license

  B

  quality

  B

  maintenance

  Enables AI assistants to pause and request user feedback through an auto-launching browser interface, where users can select or edit prompts, type responses, upload images, and auto-submit on a timer. It supports local, SSH remote, and WSL setups with session tracking, audio notifications, and multi-language web UI.

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  2

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• Relay

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  A

  license

  -Not graded

  quality

  D

  maintenance

  Adds a human-in-the-loop checkpoint to MCP-capable AI coding agents, enabling them to pause and request user feedback before executing actions.

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  8 npm

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• Clarify MCP Server

  ifmelate

  A

  license

  -Not graded

  quality

  D

  maintenance

  Enables AI agents to ask clarification questions and receive structured user input through a Human-in-the-Loop interface.

  Updated a year ago (2025-11-25 15:54 UTC)

  1

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• Interactive Feedback MCP

  nhatprx

  A

  license

  A

  quality

  D

  maintenance

  Enables AI assistants to request user feedback and confirmation to prevent speculative tool calls and reduce resource usage. It streamlines task completion by consolidating multiple potential steps into a single, feedback-aware process.

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