RRepoGEO

REPOGEO REPORT · LITE

jamubc/gemini-mcp-tool

Default branch main · commit 588e73df · scanned 6/20/2026, 6:46:55 AM

GitHub: 2,244 stars · 197 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)

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

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 jamubc/gemini-mcp-tool, 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 the README's opening to clarify its role as an AI integration server

    Why:

    CURRENT
    This is a simple Model Context Protocol (MCP) server that allows AI assistants to interact with the Gemini CLI. It enables the AI to leverage the power of Gemini's massive token window for large analysis, especially with large files and codebases using the `@` syntax for direction.
    COPY-PASTE FIX
    The `gemini-mcp-tool` is an **integration server** implementing the Model Context Protocol (MCP). It allows AI assistants (like Claude) to seamlessly interact with powerful command-line language models, specifically the Antigravity CLI (`agy`) (successor to the retired Gemini CLI). This enables AI to leverage large context windows for deep analysis of extensive files and codebases.
  • hightopics#2
    Add more specific topics to clarify the repo's integration and proxying role

    Why:

    CURRENT
    ai, claude, cli, codebase-analysis, file-analysis, gemini, mcp, model-context-protocol, npm, typescript
    COPY-PASTE FIX
    ai, claude, cli, codebase-analysis, file-analysis, gemini, model-context-protocol, npm, typescript, ai-integration, llm-integration, context-window, proxy-server
  • mediumlicense#3
    Clarify the project's license directly in the README

    Why:

    COPY-PASTE FIX
    Add a section or line in the README, for example: 'This project is licensed under [Specify License Name(s) from LICENSE file, e.g., 'a custom license combining MIT and Apache-2.0']. See the [LICENSE](LICENSE) file for full details.'

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 jamubc/gemini-mcp-tool
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Copilot Enterprise
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot Enterprise · recommended 1×
  2. AWS CodeWhisperer · recommended 1×
  3. Gemini for Google Cloud · recommended 1×
  4. Tabnine Enterprise · recommended 1×
  5. CodiumAI · recommended 1×
  • CATEGORY QUERY
    Tool for AI assistants to analyze extensive codebases using a powerful language model's large context.
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. AWS CodeWhisperer
    3. Gemini for Google Cloud
    4. Tabnine Enterprise
    5. CodiumAI
    6. Sourcegraph Cody Enterprise

    AI recommended 6 alternatives but never named jamubc/gemini-mcp-tool. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I integrate an AI assistant with a command-line tool for deep file analysis?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4/GPT-3.5 Turbo
    2. Anthropic Claude
    3. Google Gemini
    4. Mistral AI
    5. Mixtral 8x7B
    6. Hugging Face Transformers (huggingface/transformers)
    7. Llama 3
    8. Falcon
    9. `argparse`
    10. `Click` (pallets/click)
    11. `Typer` (tiangolo/typer)
    12. `cobra` (spf13/cobra)
    13. `open()` and `read()`
    14. `python-docx` (python-openxml/python-docx)
    15. `PyPDF2` (py-pdf/pypdf)
    16. `pdfminer.six` (pdfminer/pdfminer.six)
    17. `Pillow` (python-pillow/Pillow)
    18. `tesseract` (tesseract-ocr/tesseract)
    19. `pytesseract` (madmaze/pytesseract)
    20. `tree-sitter` (tree-sitter/tree-sitter)
    21. `requests` (psf/requests)
    22. `openai` (openai/openai-python)
    23. `anthropic` (anthropics/anthropic-sdk-python)
    24. `google-generativeai` (google/generative-ai-python)
    25. `langchain` (langchain-ai/langchain)
    26. `LlamaIndex` (run-llama/llama_index)

    AI recommended 26 alternatives but never named jamubc/gemini-mcp-tool. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 jamubc/gemini-mcp-tool?
    pass
    AI did not name jamubc/gemini-mcp-tool — 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?

  • If a team adopts jamubc/gemini-mcp-tool in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jamubc/gemini-mcp-tool 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 jamubc/gemini-mcp-tool solve, and who is the primary audience?
    pass
    AI did not name jamubc/gemini-mcp-tool — 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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jamubc/gemini-mcp-tool — 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