Interactive Feedback MCP
MCP server providing a human-in-the-loop feedback mechanism for AI development tools. Displays command execution results in a GUI and lets developers review outputs and provide textual feedback to AI assistants before task completion, reducing speculative tool calls.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Local-only tool with no network exposure. No auth needed but also no access control. Qt GUI dependency is a large surface area. Command execution capability requires trust.
⚡ Reliability
Best When
You use Cursor, Cline, or Windsurf and want to inject human review points into AI workflows to improve accuracy and reduce wasted tool calls.
Avoid When
You want fully automated AI workflows without human intervention, or you work in headless environments.
Use Cases
- • Reviewing AI-generated code changes before acceptance in Cursor or Cline
- • Providing iterative feedback to AI assistants during multi-step tasks
- • Reducing wasted AI tool calls by injecting human checkpoints
- • Running and reviewing command outputs with AI context
Not For
- • Headless/CI environments (requires GUI)
- • Automated pipelines without human oversight
- • Non-MCP AI tool integrations
Interface
Authentication
No auth required. Local tool only.
Pricing
MIT license.
Agent Metadata
Known Gotchas
- ⚠ Requires Qt GUI - won't work in headless or SSH environments
- ⚠ Single tool (interactive_feedback) - very focused scope
- ⚠ Requires prompt engineering to ensure AI actually calls the tool
- ⚠ 315 forks vs 1686 stars suggests many custom modifications needed
- ⚠ Python 3.11+ and uv required
Full Evaluation Report
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Package Brief
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Scores are editorial opinions as of 2026-03-08.