RRepoGEO

REPOGEO REPORT · LITE

dsphper/lanhu-mcp

Default branch main · commit 74c6ac53 · scanned 5/8/2026, 12:57:06 PM

GitHub: 1,299 stars · 144 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 dsphper/lanhu-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
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-programming, model-context-protocol, mcp-server, lanhu-integration, design-to-code, ai-assistant-collaboration, team-knowledge-base, frontend-generation, axure-parser, ui-automation
  • highreadme#2
    Reposition the README's opening tagline to clarify core function

    Why:

    CURRENT
    让所有 AI 助手共享团队知识，打破 AI IDE 孤岛lanhumcp | 蓝湖mcp | lanhu-mcp | 蓝湖AI助手 | 蓝湖skills | Lanhu AI Integration
    COPY-PASTE FIX
    全球首个为 AI 编程时代设计的团队协作 MCP 服务器，让所有 AI 助手共享团队知识和设计上下文，打破 AI IDE 孤岛。自动分析需求，自动编写前后端代码，下载切图。
  • mediumhomepage#3
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://modelcontextprotocol.io/

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 dsphper/lanhu-mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Confluence
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Confluence · recommended 1×
  2. Jira · recommended 1×
  3. GitHub Copilot Enterprise · recommended 1×
  4. langchain-ai/langchain · recommended 1×
  5. run-llama/llama_index · recommended 1×
  • CATEGORY QUERY
    How can AI coding assistants access shared team knowledge and design context?
    you: not recommended
    AI recommended (in order):
    1. Confluence
    2. Jira
    3. GitHub Copilot Enterprise
    4. LangChain (langchain-ai/langchain)
    5. LlamaIndex (run-llama/llama_index)
    6. Slab
    7. Notion
    8. Guru
    9. Pinecone
    10. Weaviate (weaviate/weaviate)
    11. ChromaDB (chroma-core/chroma)
    12. OpenAI's `text-embedding-ada-002`
    13. GPT-4
    14. Claude 3
    15. Sourcegraph (sourcegraph/sourcegraph)
    16. OpenGrok (OpenGrok/OpenGrok)
    17. Storybook (storybookjs/storybook)
    18. Zeroheight

    AI recommended 18 alternatives but never named dsphper/lanhu-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools automatically analyze design requirements and generate frontend code and assets?
    you: not recommended
    AI recommended (in order):
    1. Locofy.ai
    2. Anima
    3. Gleap
    4. Uizard
    5. DhiWise
    6. TeleportHQ

    AI recommended 6 alternatives but never named dsphper/lanhu-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 dsphper/lanhu-mcp?
    pass
    AI did not name dsphper/lanhu-mcp — 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 dsphper/lanhu-mcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dsphper/lanhu-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 dsphper/lanhu-mcp solve, and who is the primary audience?
    pass
    AI named dsphper/lanhu-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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