RRepoGEO

REPOGEO REPORT · LITE

mem9-ai/mem9

Default branch main · commit 6467e3dc · scanned 5/8/2026, 2:12:58 PM

GitHub: 1,076 stars · 111 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 mem9-ai/mem9, 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
  • highabout#1
    Broaden the repository description

    Why:

    CURRENT
    Unlimited memory for OpenClaw
    COPY-PASTE FIX
    Persistent memory for AI agents across sessions and machines, with shared memory for multi-agent workflows.
  • mediumhomepage#2
    Add the project homepage URL

    Why:

    COPY-PASTE FIX
    https://mem9.ai

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 mem9-ai/mem9
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pinecone
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pinecone · recommended 2×
  2. PostgreSQL · recommended 2×
  3. Chroma · recommended 1×
  4. Redis · recommended 1×
  5. pgvector · recommended 1×
  • CATEGORY QUERY
    How can I give my AI agents persistent memory across multiple sessions?
    you: not recommended
    AI recommended (in order):
    1. Chroma
    2. Pinecone
    3. Redis
    4. PostgreSQL
    5. pgvector
    6. LangChain
    7. Faiss

    AI recommended 7 alternatives but never named mem9-ai/mem9. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools provide shared memory and recall for collaborative AI agent workflows?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Pinecone
    3. Weaviate (weaviate/weaviate)
    4. ChromaDB (chroma-core/chroma)
    5. LlamaIndex (run-llama/llama_index)
    6. Redis (redis/redis)
    7. RedisJSON (RedisJSON/RedisJSON)
    8. Redis Stack
    9. Faiss (facebookresearch/faiss)
    10. Milvus (milvus-io/milvus)
    11. Zilliz
    12. PostgreSQL
    13. pgvector (pgvector/pgvector)
    14. NFS
    15. S3
    16. Google Cloud Storage

    AI recommended 16 alternatives but never named mem9-ai/mem9. 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 mem9-ai/mem9?
    pass
    AI named mem9-ai/mem9 explicitly

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

  • If a team adopts mem9-ai/mem9 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mem9-ai/mem9 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 mem9-ai/mem9 solve, and who is the primary audience?
    pass
    AI named mem9-ai/mem9 explicitly

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite