RRepoGEO

REPOGEO REPORT · LITE

supabase/mcp

Default branch main · commit 71e48cce · scanned 6/5/2026, 9:41:50 AM

GitHub: 2,719 stars · 362 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 supabase/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
    Update the README's H1 to explicitly state the full project name

    Why:

    CURRENT
    # Supabase MCP Server
    COPY-PASTE FIX
    # Supabase Model Context Protocol (MCP) Server
  • hightopics#2
    Add descriptive topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    supabase, llm, ai, model-context-protocol, mcp, database-connector, data-interaction, assistant-integration, postgres
  • mediumreadme#3
    Strengthen the README's opening paragraph to clarify problem and audience

    Why:

    CURRENT
    > Connect your Supabase projects to Cursor, Claude, Windsurf, and other AI assistants. The Model Context Protocol (MCP) standardizes how Large Language Models (LLMs) talk to external services like Supabase. It connects AI assistants directly with your Supabase project and allows them to perform tasks like managing tables, fetching config, and querying data.
    COPY-PASTE FIX
    The Supabase Model Context Protocol (MCP) Server enables seamless, secure integration between your Supabase projects and various AI assistants like Cursor, Claude, and Windsurf. It standardizes how Large Language Models (LLMs) interact with external services, allowing them to directly manage tables, fetch configurations, and query data within your Supabase project.

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 supabase/mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. SQLAlchemy · recommended 1×
  4. Hugging Face Transformers · recommended 1×
  5. DB-GPT · recommended 1×
  • CATEGORY QUERY
    How can I connect my AI assistant to manage and query data in my database?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. SQLAlchemy
    4. Hugging Face Transformers
    5. DB-GPT
    6. Microsoft Semantic Kernel
    7. DataStax Astra DB

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

    Show full AI answer
  • CATEGORY QUERY
    What's the best way to integrate LLMs with existing backend services for data interaction?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI Functions
    4. Google's Gemini
    5. Zapier NLA
    6. AWS Lambda
    7. AWS API Gateway
    8. Google Cloud Functions
    9. Google Cloud API Gateway
    10. Azure Functions
    11. Azure API Management
    12. FastAPI
    13. Flask
    14. Pydantic
    15. GraphQL
    16. Apollo Client

    AI recommended 16 alternatives but never named supabase/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 supabase/mcp?
    pass
    AI named supabase/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 supabase/mcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named supabase/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 supabase/mcp solve, and who is the primary audience?
    pass
    AI named supabase/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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