RRepoGEO

REPOGEO REPORT · LITE

iannuttall/mcp-boilerplate

Default branch main · commit e248a9fd · scanned 5/10/2026, 7:28:08 PM

GitHub: 1,022 stars · 196 forks

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 iannuttall/mcp-boilerplate, 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' in README title and opening paragraph

    Why:

    CURRENT
    # MCP Boilerplate: Simple Setup Guide
    This project helps you create your own remote MCP server on Cloudflare with user login and payment options.
    COPY-PASTE FIX
    # Cloudflare AI Assistant Boilerplate (MCP): Simple Setup Guide
    This project helps you create your own remote **AI assistant server (referred to as MCP server)** on Cloudflare with user login and payment options. It's designed for building monetized AI tools that work with platforms like Cursor and Claude.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ["cloudflare", "ai", "assistant", "boilerplate", "serverless", "stripe", "authentication", "oauth", "monetization", "web-development", "nodejs"]
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://[YOUR_PROJECT_DEMO_OR_DOCS_URL_HERE]

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 iannuttall/mcp-boilerplate
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
vercel/next.js
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. vercel/next.js · recommended 2×
  2. Vercel · recommended 2×
  3. supabase/supabase · recommended 2×
  4. Firestore · recommended 2×
  5. Stripe · recommended 1×
  • CATEGORY QUERY
    How to build a custom AI assistant tool with user login and payment features?
    you: not recommended
    AI recommended (in order):
    1. Next.js (vercel/next.js)
    2. Vercel
    3. Stripe
    4. OpenAI API
    5. Supabase (supabase/supabase)
    6. PostgreSQL
    7. Django (django/django)
    8. Django REST Framework (encode/django-rest-framework)
    9. React (facebook/react)
    10. Vue.js (vuejs/core)
    11. Firebase Authentication
    12. Firestore
    13. Firebase Cloud Functions
    14. Ruby on Rails (rails/rails)
    15. AWS Amplify
    16. AWS Cognito
    17. AWS AppSync
    18. API Gateway
    19. DynamoDB
    20. Aurora
    21. AWS Lambda

    AI recommended 21 alternatives but never named iannuttall/mcp-boilerplate. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a serverless boilerplate to create monetized AI services with user authentication.
    you: not recommended
    AI recommended (in order):
    1. Amplify Framework (aws-amplify/amplify-js)
    2. Serverless Framework (serverless/serverless)
    3. Next.js (vercel/next.js)
    4. Vercel
    5. Supabase (supabase/supabase)
    6. Auth0
    7. AWS Serverless Application Model (aws/aws-sam-cli)
    8. Firebase
    9. Google Cloud Functions
    10. Firestore
    11. Realtime Database
    12. Azure Static Web Apps
    13. Azure Functions
    14. Azure AD B2C

    AI recommended 14 alternatives but never named iannuttall/mcp-boilerplate. 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 iannuttall/mcp-boilerplate?
    pass
    AI did not name iannuttall/mcp-boilerplate — 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 iannuttall/mcp-boilerplate in production, what risks or prerequisites should they evaluate first?
    pass
    AI named iannuttall/mcp-boilerplate 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 iannuttall/mcp-boilerplate solve, and who is the primary audience?
    pass
    AI named iannuttall/mcp-boilerplate explicitly

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

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iannuttall/mcp-boilerplate — 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