RRepoGEO

REPOGEO REPORT · LITE

Minidoracat/mcp-feedback-enhanced

Default branch main · commit 541ca1e5 · scanned 6/27/2026, 1:57:21 PM

GitHub: 3,788 stars · 351 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Minidoracat/mcp-feedback-enhanced, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 and opening sentence to clarify AI development focus

    Why:

    CURRENT
    # MCP Feedback Enhanced

**🌐 Language / 語言切換:English** | [繁體中文](README.zh-TW.md) | [简体中文](README.zh-CN.md)

**Original Author:** Fábio Ferreira | Original Project ⭐
**Enhanced Fork:** Minidoracat
**UI Design Reference:** sanshao85/mcp-feedback-collector

## 🎯 Core Concept

This is an MCP server that establishes **feedback-oriented development workflows**, providing **Web UI and Desktop Application** dual interface options...
    COPY-PASTE FIX
    # AI Development Feedback & Command Server (MCP Enhanced)

**🌐 Language / 語言切換:English** | [繁體中文](README.zh-TW.md) | [简体中文](README.zh-CN.md)

**Original Author:** Fábio Ferreira | Original Project ⭐
**Enhanced Fork:** Minidoracat
**UI Design Reference:** sanshao85/mcp-feedback-collector

## 🎯 Core Concept

This enhanced server establishes **feedback-oriented development workflows for AI agents and models**, providing **Web UI and Desktop Application** dual interface options...
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    ai-development, llm-feedback, agent-feedback, feedback-loop, cross-platform, web-ui, desktop-app, tauri, wsl, remote-development
  • mediumreadme#3
    Clarify existing license in README

    Why:

    COPY-PASTE FIX
    Add a section to your README, for example: `## License` followed by `This project is licensed under the terms found in the [LICENSE](LICENSE) file. Please refer to the file for full details on the applicable license(s).`

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface Minidoracat/mcp-feedback-enhanced
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Weights & Biases
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Weights & Biases · recommended 2×
  2. Scale AI · recommended 1×
  3. Appen · recommended 1×
  4. Amazon Mechanical Turk · recommended 1×
  5. Databricks · recommended 1×
  • CATEGORY QUERY
    How can I integrate user feedback directly into AI-driven development workflows for confirmation?
    you: not recommended
    AI recommended (in order):
    1. Scale AI
    2. Appen
    3. Amazon Mechanical Turk
    4. Databricks
    5. Weights & Biases
    6. MLflow (mlflow/mlflow)
    7. Label Studio (heartexlabs/label-studio)
    8. Prodigy
    9. PostgreSQL
    10. MongoDB
    11. S3
    12. DVC (iterative/dvc)
    13. Git LFS (git-lfs/git-lfs)

    AI recommended 13 alternatives but never named Minidoracat/mcp-feedback-enhanced. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools provide cross-platform desktop and web interfaces for AI development feedback in remote environments?
    you: not recommended
    AI recommended (in order):
    1. Streamlit
    2. Gradio
    3. Weights & Biases
    4. Dash by Plotly
    5. Voila
    6. Panel
    7. Label Studio

    AI recommended 7 alternatives but never named Minidoracat/mcp-feedback-enhanced. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of Minidoracat/mcp-feedback-enhanced?
    pass
    AI named Minidoracat/mcp-feedback-enhanced explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Minidoracat/mcp-feedback-enhanced in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Minidoracat/mcp-feedback-enhanced explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo Minidoracat/mcp-feedback-enhanced solve, and who is the primary audience?
    pass
    AI did not name Minidoracat/mcp-feedback-enhanced — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Minidoracat/mcp-feedback-enhanced — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite