RRepoGEO

REPOGEO REPORT · LITE

homeassistant-ai/ha-mcp

Default branch master · commit e74031e0 · scanned 6/26/2026, 10:31:50 PM

GitHub: 3,660 stars · 148 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)

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

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 homeassistant-ai/ha-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
    Reposition README H1 to emphasize AI integration

    Why:

    CURRENT
    # The Unofficial and Awesome Home Assistant MCP Server
    COPY-PASTE FIX
    # Home Assistant AI Integration Server (MCP)
  • mediumhomepage#2
    Add project homepage to repository About section

    Why:

    COPY-PASTE FIX
    https://homeassistant-ai.github.io/ha-mcp/
  • mediumtopics#3
    Add integration-focused topics

    Why:

    CURRENT
    ai, claude, hacs, home-assistant, home-automation, llm, mcp, model-context-protocol
    COPY-PASTE FIX
    ai, claude, hacs, home-assistant, home-automation, llm, mcp, model-context-protocol, smart-home-integration, llm-integration, ai-assistant-integration

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 homeassistant-ai/ha-mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
home-assistant/core
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. home-assistant/core · recommended 3×
  2. Amazon Alexa · recommended 2×
  3. Google Assistant · recommended 2×
  4. openhab/openhab-core · recommended 2×
  5. Apple HomeKit · recommended 2×
  • CATEGORY QUERY
    Seeking a solution for natural language interaction with smart home devices via AI.
    you: not recommended
    AI recommended (in order):
    1. Home Assistant (home-assistant/core)
    2. Nabu Casa Cloud
    3. Assist (home-assistant/core)
    4. Amazon Alexa
    5. Alexa Skills Kit (ASK)
    6. Google Assistant
    7. Actions on Google
    8. OpenHAB (openhab/openhab-core)
    9. Mycroft AI (MycroftAI/mycroft-core)
    10. Apple HomeKit
    11. Siri Shortcuts
    12. Rhasspy (rhasspy/rhasspy)

    AI recommended 12 alternatives but never named homeassistant-ai/ha-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to integrate large language models with existing smart home control systems?
    you: not recommended
    AI recommended (in order):
    1. Home Assistant (home-assistant/core)
    2. OpenAI GPT-3.5/GPT-4
    3. Llama 2/3
    4. Ollama (ollama/ollama)
    5. OpenWebUI (open-webui/open-webui)
    6. IFTTT (If This Then That)
    7. Node-RED (node-red/node-red)
    8. Llama.cpp (ggerganov/llama.cpp)
    9. SmartThings
    10. Google Assistant
    11. Amazon Alexa
    12. Google Cloud Function
    13. AWS Lambda
    14. Homebridge (homebridge/homebridge)
    15. Apple HomeKit
    16. OpenHAB (openhab/openhab-core)

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