RRepoGEO

REPOGEO REPORT · LITE

yjacquin/fast-mcp

Default branch main · commit 7ec08b91 · scanned 5/15/2026, 7:41:55 PM

GitHub: 1,174 stars · 106 forks

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
  • highabout#1
    Update the 'About' description to explicitly define Model Context Protocol

    Why:

    CURRENT
    A Ruby Implementation of the Model Context Protocol
    COPY-PASTE FIX
    A Ruby implementation of the Model Context Protocol (MCP) for connecting AI models and LLMs to your Ruby applications, enabling secure function calling and data sharing.
  • hightopics#2
    Add more specific topics to improve AI categorization

    Why:

    CURRENT
    ai, llm, mcp, rack, ruby
    COPY-PASTE FIX
    ai, llm, mcp, rack, ruby, model-context-protocol, llm-integration, ai-tools, function-calling, api-integration
  • mediumreadme#3
    Add a clarifying sentence to the README's opening

    Why:

    COPY-PASTE FIX
    Fast MCP provides a robust, Ruby-native implementation of the Model Context Protocol (MCP), a standard for enabling AI models to securely interact with your application's functions and data.

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-openai
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. openai/ruby-openai · recommended 1×
  2. lostisland/faraday · recommended 1×
  3. grpc/grpc-ruby · recommended 1×
  4. ruby-tensorflow/ruby-tf · recommended 1×
  5. pytorch-ruby/pytorch-ruby · recommended 1×
  • CATEGORY QUERY
    Seeking a straightforward way to connect AI models to a Ruby application backend.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Ruby Client (openai/ruby-openai)
    2. faraday (lostisland/faraday)
    3. grpc (grpc/grpc-ruby)
    4. ruby-tf (ruby-tensorflow/ruby-tf)
    5. pytorch-ruby (pytorch-ruby/pytorch-ruby)
    6. rest-client (rest-client/rest-client)
    7. net/http

    AI recommended 7 alternatives but never named yjacquin/fast-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I enable LLMs to invoke Ruby application functions securely and easily?
    you: not recommended
    AI recommended (in order):
    1. OpenAPI
    2. rswag (rswag/rswag)
    3. openapi_parser (ruby-json-schema/openapi_parser)
    4. Ruby on Rails (rails/rails)
    5. ActiveModel::Serializer (rails-api/active_model_serializers)
    6. jsonapi-serializer (jsonapi-serializer/jsonapi-serializer)
    7. Devise (heartcombo/devise)
    8. JWT (jwt/ruby-jwt)
    9. Pundit (varvet/pundit)
    10. CanCanCan (CanCanCommunity/cancancan)
    11. Sidekiq (mperham/sidekiq)
    12. Resque (resque/resque)
    13. Delayed Job (collectiveidea/delayed_job)
    14. LangChain.rb (andreibondarev/langchainrb)

    AI recommended 14 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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  • Brand-free category queries5 vs 2 in Lite
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