RRepoGEO

REPOGEO REPORT · LITE

memvid/claude-brain

Default branch main · commit 5df71f77 · scanned 6/10/2026, 2:17:16 PM

GitHub: 501 stars · 49 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 memvid/claude-brain, 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
    Emphasize 'no database' and 'Claude-specific' in the README's opening

    Why:

    CURRENT
    ### Give Claude Code photographic memory.
    COPY-PASTE FIX
    ### Give Claude Code photographic memory.

Unlike vector databases, complex frameworks, or generic file storage, `claude-brain` provides Claude Code with persistent, photographic memory in a single, portable file, requiring no database or cloud dependencies.
  • mediumtopics#2
    Add topics emphasizing 'no database' and 'AI coding assistant' specific memory

    Why:

    CURRENT
    ai-tools, anthropic, claude, claude-agents, claude-ai, claude-code, claude-skills, context-window, developer-tools, llm-memory, long-term-memory, memvid, persistent-memory, portable, rag, rust, single-file
    COPY-PASTE FIX
    ai-tools, anthropic, claude, claude-agents, claude-ai, claude-code, claude-skills, context-window, developer-tools, llm-memory, long-term-memory, memvid, persistent-memory, portable, rag, rust, single-file, no-database, local-first-ai, ai-coding-memory
  • lowreadme#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

`claude-brain` stands apart from common AI memory solutions:

- **Vector Databases (e.g., Pinecone, Weaviate, Qdrant):** `claude-brain` requires no external database, offering a single, portable `.mv2` file for memory, ideal for local development and easy sharing.
- **LLM Frameworks (e.g., LangChain, LlamaIndex):** While these frameworks offer broad LLM orchestration, `claude-brain` focuses specifically on deep, persistent memory for Claude Code, without the overhead of a full framework.
- **Generic File Storage (e.g., SQLite, DuckDB, JSON):** Unlike general-purpose data storage, `claude-brain` is purpose-built for semantic memory, optimized for Claude's context, and designed for sub-millisecond retrieval of relevant code and conversation history.

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 memvid/claude-brain
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pinecone
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Pinecone · recommended 1×
  2. Weaviate · recommended 1×
  3. Qdrant · recommended 1×
  4. LangChain · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    How to give an AI coding assistant long-term memory across development sessions?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. Weaviate
    3. Qdrant
    4. LangChain
    5. LlamaIndex
    6. OpenAI's `text-embedding-ada-002`
    7. Google's `text-embedding-004`
    8. GPT-4
    9. Claude 3
    10. Gemini
    11. GitHub Copilot Chat
    12. Cursor
    13. Continue.dev
    14. Chroma
    15. FAISS
    16. Git
    17. Obsidian
    18. Notion
    19. Confluence
    20. PostgreSQL
    21. MongoDB

    AI recommended 21 alternatives but never named memvid/claude-brain. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are options for a portable, single-file persistent memory solution for AI agents?
    you: not recommended
    AI recommended (in order):
    1. SQLite
    2. DuckDB (duckdb/duckdb)
    3. TinyDB (msiemens/tinydb)
    4. Pickle
    5. JSON/YAML Files
    6. HDF5 (HDFGroup/hdf5)
    7. LMDB

    AI recommended 7 alternatives but never named memvid/claude-brain. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 memvid/claude-brain?
    pass
    AI named memvid/claude-brain explicitly

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

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