RRepoGEO

REPOGEO REPORT · LITE

mem0ai/mem0-mcp

Default branch main · commit 624024de · scanned 5/31/2026, 7:28:20 PM

GitHub: 655 stars · 144 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 mem0ai/mem0-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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    Archived: A Model Context Protocol (MCP) server that wrapped the Mem0 Memory API for AI agents to add, search, update, and delete long-term memories. An official cloud-hosted MCP server is now available.
  • mediumreadme#2
    Clarify archived status in the README's first descriptive paragraph

    Why:

    CURRENT
    `mem0-mcp-server` wraps the official Mem0 Memory API as a Model Context Protocol (MCP) server so any MCP-compatible client (Claude Desktop, Cursor, custom agents) can add, search, update, and delete long-term memories.
    COPY-PASTE FIX
    `mem0-mcp-server` was an open-source Model Context Protocol (MCP) server that wrapped the Mem0 Memory API, allowing MCP-compatible clients (like Claude Desktop or Cursor) to add, search, update, and delete long-term memories for AI agents. This project is now archived; an official cloud-hosted MCP server is available.

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 mem0ai/mem0-mcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. Pinecone · recommended 2×
  3. Weaviate · recommended 2×
  4. LlamaIndex · recommended 2×
  5. Redis · recommended 2×
  • CATEGORY QUERY
    How can I give my AI agent long-term memory capabilities for conversational context?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Pinecone
    3. Chroma
    4. Weaviate
    5. LlamaIndex
    6. Redis
    7. RedisJSON
    8. RediSearch
    9. PostgreSQL
    10. pgvector
    11. MongoDB
    12. MongoDB Atlas
    13. Faiss
    14. Qdrant

    AI recommended 14 alternatives but never named mem0ai/mem0-mcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What framework helps integrate external memory management with large language models?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. Faiss
    5. Pinecone
    6. Weaviate
    7. Qdrant
    8. Redis
    9. NumPy
    10. Scikit-learn
    11. psycopg2
    12. pymongo

    AI recommended 12 alternatives but never named mem0ai/mem0-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
    fail

    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 mem0ai/mem0-mcp?
    pass
    AI named mem0ai/mem0-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 mem0ai/mem0-mcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mem0ai/mem0-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 mem0ai/mem0-mcp solve, and who is the primary audience?
    pass
    AI named mem0ai/mem0-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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mem0ai/mem0-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