RRepoGEO

REPOGEO REPORT · LITE

dsphper/lanhu-mcp

Default branch main · commit 92a18200 · scanned 6/18/2026, 4:31:27 AM

GitHub: 1,725 stars · 193 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify "MCP" and core function in README opening

    Why:

    COPY-PASTE FIX
    Insert this sentence immediately after the main title/tagline in the README: "This is the world's first Model Context Protocol (MCP) server designed for the AI programming era, acting as a team collaboration hub that automatically analyzes requirements and generates frontend/backend code."
  • mediumhomepage#2
    Add a 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
GitHub Copilot Enterprise
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot Enterprise · recommended 1×
  2. GitLab Duo Enterprise · recommended 1×
  3. Cody · recommended 1×
  4. OpenAI API · recommended 1×
  5. Pinecone · recommended 1×
  • CATEGORY QUERY
    Seeking a collaboration server to share context and knowledge among AI coding tools.
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. GitLab Duo Enterprise
    3. Cody
    4. OpenAI API
    5. Pinecone
    6. Weaviate
    7. Qdrant
    8. Microsoft Azure AI Studio
    9. Google Cloud Vertex AI
    10. Jira Software
    11. Jira Product Discovery

    AI recommended 11 alternatives but never named dsphper/lanhu-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can AI assistants automatically analyze design mockups and generate frontend code from them?
    you: not recommended
    AI recommended (in order):
    1. Locofy.ai
    2. Anima
    3. DhiWise
    4. Uizard
    5. Gleap.dev
    6. OpenAI's GPT-4V (Vision)
    7. DALL-E 3
    8. Microsoft's Sketch2Code

    AI recommended 8 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 named dsphper/lanhu-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 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 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?

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dsphper/lanhu-mcp — 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