RRepoGEO

REPOGEO REPORT · LITE

yjacquin/fast-mcp

Default branch main · commit 7ec08b91 · scanned 6/26/2026, 2:21:41 PM

GitHub: 1,180 stars · 106 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
35 /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
3 / 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 yjacquin/fast-mcp, 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
    Clarify 'MCP' acronym and domain in README H1 and opening paragraph

    Why:

    CURRENT
    # Fast MCP 🚀

<div align="center">
  <h3>Connect AI models to your Ruby applications with ease</h3>
    COPY-PASTE FIX
    # Fast MCP (Model Context Protocol) 🚀

<div align="center">
  <h3>Connect AI models to your Ruby applications with ease using the Model Context Protocol</h3>
  • highhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    [Add the official documentation or project website URL here]
  • mediumtopics#3
    Expand and refine repository topics to reinforce AI integration

    Why:

    CURRENT
    ai, llm, mcp, rack, ruby
    COPY-PASTE FIX
    ai, llm, mcp, rack, ruby, ai-integration, llm-tools, ruby-ai, model-context-protocol, function-calling

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 yjacquin/fast-mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Ruby Gem
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Ruby Gem · recommended 1×
  2. LangChain.rb · recommended 1×
  3. Google Cloud Ruby Client · recommended 1×
  4. Anthropic Ruby SDK · recommended 1×
  5. Hugging Face `inference-api-ruby` gem · recommended 1×
  • CATEGORY QUERY
    How to easily integrate large language models with a Ruby on Rails application?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Ruby Gem
    2. LangChain.rb
    3. Google Cloud Ruby Client
    4. Anthropic Ruby SDK
    5. Hugging Face `inference-api-ruby` gem
    6. `ruby-llm` gem
    7. HTTParty
    8. Faraday

    AI recommended 8 alternatives but never named yjacquin/fast-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Ruby library to allow AI models to securely call functions within my application?
    you: not recommended
    AI recommended (in order):
    1. ruby-openai (openai/ruby-openai)
    2. langchainrb (andreibondarev/langchainrb)
    3. dry-schema (dry-rb/dry-schema)
    4. dry-validation (dry-rb/dry-validation)
    5. Pundit (varvet/pundit)
    6. CanCanCan (CanCanCommunity/cancancan)

    AI recommended 6 alternatives but never named yjacquin/fast-mcp. 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 yjacquin/fast-mcp?
    pass
    AI named yjacquin/fast-mcp explicitly

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

  • If a team adopts yjacquin/fast-mcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yjacquin/fast-mcp 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 yjacquin/fast-mcp solve, and who is the primary audience?
    pass
    AI named yjacquin/fast-mcp explicitly

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

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yjacquin/fast-mcp — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite