RRepoGEO

REPOGEO REPORT · LITE

doobidoo/mcp-memory-service

Default branch main · commit 2e193783 · scanned 5/17/2026, 1:56:28 AM

GitHub: 1,851 stars · 281 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 doobidoo/mcp-memory-service, 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
    Clarify 'MCP' and 'persistent' in the README's opening

    Why:

    CURRENT
    ## Persistent Shared Memory for AI Agent Pipelines
    COPY-PASTE FIX
    ## Persistent Shared Memory for AI Agent Pipelines

This service implements the Model Context Protocol (MCP) to provide *persistent*, not in-memory, storage for AI agent conversations and knowledge.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add the official project homepage URL to the repository's 'About' section.
  • mediumreadme#3
    Emphasize knowledge graph and semantic search capabilities in the README's top section

    Why:

    CURRENT
    Agents store decisions, share causal knowledge graphs, and retrieve context in 5ms
    COPY-PASTE FIX
    Agents store decisions, share causal knowledge graphs, and retrieve context in 5ms. Leverage its built-in knowledge graph and semantic search capabilities for advanced context retrieval in your AI agents.

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 doobidoo/mcp-memory-service
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
weaviate/weaviate
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. weaviate/weaviate · recommended 2×
  2. milvus-io/milvus · recommended 2×
  3. Pinecone · recommended 1×
  4. Weaviate · recommended 1×
  5. Qdrant · recommended 1×
  • CATEGORY QUERY
    How to implement long-term persistent memory for my AI agentic workflows?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. Weaviate
    3. Qdrant
    4. Chroma
    5. Redis with Redis Stack (RediSearch/RedisJSON)
    6. PostgreSQL with pgvector
    7. MongoDB Atlas Vector Search

    AI recommended 7 alternatives but never named doobidoo/mcp-memory-service. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an open-source knowledge graph with semantic search for AI agent context retrieval.
    you: not recommended
    AI recommended (in order):
    1. Neo4j (neo4j/neo4j)
    2. Neo4j AuraDS
    3. TypeDB (vaticle/typedb)
    4. TypeQL
    5. Weaviate (weaviate/weaviate)
    6. Milvus (milvus-io/milvus)
    7. RDFox
    8. SPARQL
    9. SHACL
    10. ArangoDB (arangodb/arangodb)
    11. AQL
    12. ArangoSearch
    13. DGL (dmlc/dgl)
    14. Weaviate (weaviate/weaviate)
    15. Milvus (milvus-io/milvus)

    AI recommended 15 alternatives but never named doobidoo/mcp-memory-service. 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 doobidoo/mcp-memory-service?
    pass
    AI named doobidoo/mcp-memory-service explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of doobidoo/mcp-memory-service. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/doobidoo/mcp-memory-service.svg)](https://repogeo.com/en/r/doobidoo/mcp-memory-service)
HTML
<a href="https://repogeo.com/en/r/doobidoo/mcp-memory-service"><img src="https://repogeo.com/badge/doobidoo/mcp-memory-service.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

doobidoo/mcp-memory-service — 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