RRepoGEO

REPOGEO REPORT · LITE

janwilmake/openapi-mcp-server

Default branch main · commit 23c6986f · scanned 6/8/2026, 12:07:56 PM

GitHub: 893 stars · 94 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 janwilmake/openapi-mcp-server, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    openapi, ai-agent, llm, model-context-protocol, api-search, natural-language-processing, claude, cursor
  • highreadme#2
    Reposition the README's opening sentence to clarify its core purpose for AI agents

    Why:

    CURRENT
    # OpenAPI MCP Server

A Model Context Protocol (MCP) server for Claude/Cursor that enables searching and exploring OpenAPI specifications through oapis.org.
    COPY-PASTE FIX
    # OpenAPI MCP Server

A Model Context Protocol (MCP) server designed to empower AI agents (like Claude/Cursor) to understand, search, and interact with complex OpenAPI specifications using simple natural language, powered by oapis.org.
  • mediumreadme#3
    Explicitly state the core differentiator for AI agents in the README

    Why:

    COPY-PASTE FIX
    ## Why OpenAPI MCP Server?

Unlike generic API tools or LLM frameworks, OpenAPI MCP Server specifically translates complex OpenAPI schemas into a simplified, queryable format that AI agents can easily understand and navigate. It acts as a dedicated interpreter, enabling agents to intelligently explore API capabilities and retrieve precise operation details without needing to parse raw specifications.

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 janwilmake/openapi-mcp-server
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAPITools/openapi-generator
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAPITools/openapi-generator · recommended 1×
  2. swagger-api/swagger-codegen · recommended 1×
  3. stoplightio/prism · recommended 1×
  4. speakeasy-api/speakeasy · recommended 1×
  5. Postman · recommended 1×
  • CATEGORY QUERY
    How can an AI agent understand and interact with complex OpenAPI specifications easily?
    you: not recommended
    AI recommended (in order):
    1. OpenAPI Generator (OpenAPITools/openapi-generator)
    2. Swagger Codegen (swagger-api/swagger-codegen)
    3. Prism (stoplightio/prism)
    4. Speakeasy (speakeasy-api/speakeasy)
    5. Postman
    6. Redoc (Redocly/redoc)
    7. openapi-parser
    8. swagger-parser (APIDevTools/swagger-parser)

    AI recommended 8 alternatives but never named janwilmake/openapi-mcp-server. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help AI agents navigate and summarize API documentation using natural language?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API (GPT-4, GPT-3.5 Turbo)
    2. LangChain
    3. LlamaIndex
    4. Hugging Face Transformers
    5. BERT
    6. T5
    7. BART
    8. SpaCy
    9. NLTK
    10. Haystack (deepset.ai)
    11. Elasticsearch
    12. Sentence-BERT
    13. OpenAI Embeddings
    14. Pinecone
    15. GPT-4

    AI recommended 15 alternatives but never named janwilmake/openapi-mcp-server. 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 janwilmake/openapi-mcp-server?
    pass
    AI did not name janwilmake/openapi-mcp-server — 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 janwilmake/openapi-mcp-server in production, what risks or prerequisites should they evaluate first?
    pass
    AI named janwilmake/openapi-mcp-server 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 janwilmake/openapi-mcp-server solve, and who is the primary audience?
    pass
    AI named janwilmake/openapi-mcp-server explicitly

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

Embed your GEO score

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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
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