RRepoGEO

REPOGEO REPORT · LITE

mnemox-ai/tradememory-protocol

Default branch master · commit bc9cb0b1 · scanned 5/29/2026, 4:07:07 AM

GitHub: 1,039 stars · 130 forks

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 mnemox-ai/tradememory-protocol, 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 opening to clearly state niche and differentiate from generic databases

    Why:

    CURRENT
    The AI trading stack is missing a layer. Every MCP server handles execution — placing orders, fetching prices, reading charts. **None handle memory.** Your agent can buy 100 shares of AAPL but can't answer: "What happened last time I bought AAPL in this condition?"TradeMemory is the memory layer.** One `pip install`, and your AI agent remembers every trade, every outcome, every mistake — with SHA-256 tamper-proof audit trail.
    COPY-PASTE FIX
    The AI trading stack is missing a layer. Every MCP server handles execution — placing orders, fetching prices, reading charts. **None handle memory.** Your agent can buy 100 shares of AAPL but can't answer: "What happened last time I bought AAPL in this condition?"TradeMemory is the memory layer.** Unlike generic databases or broad enterprise financial platforms, it's purpose-built as a tamper-proof audit trail and persistent memory protocol specifically for AI trading agents. One `pip install`, and your AI agent remembers every trade, every outcome, every mistake — with SHA-256 tamper-proof audit trail.
  • mediumtopics#2
    Add compliance and audit-related topics

    Why:

    CURRENT
    ai-agents, claude, crypto, evolution-engine, forex, mcp, mcp-server, memory, mt5, outcome-weighted-memory, trading
    COPY-PASTE FIX
    ai-agents, claude, crypto, evolution-engine, forex, mcp, mcp-server, memory, mt5, outcome-weighted-memory, trading, audit-trail, regulatory-compliance, algorithmic-trading-compliance, ai-governance
  • lowreadme#3
    Add a 'Comparison to Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    Create a new section in the README, e.g., 'Comparison to Alternatives', that explicitly outlines how TradeMemory Protocol differs from: 1. Generic databases (e.g., PostgreSQL, MongoDB) by offering specialized, outcome-weighted recall and tamper-proof audit trails for AI trading. 2. Broad enterprise financial platforms (e.g., Symphony, Murex) by providing a focused, agent-centric memory and compliance layer rather than a full trading system.

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 mnemox-ai/tradememory-protocol
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PostgreSQL
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PostgreSQL · recommended 1×
  2. SQLAlchemy · recommended 1×
  3. MongoDB · recommended 1×
  4. Couchbase · recommended 1×
  5. InfluxDB · recommended 1×
  • CATEGORY QUERY
    How to implement persistent memory and decision logging for my AI trading agent?
    you: not recommended
    AI recommended (in order):
    1. PostgreSQL
    2. SQLAlchemy
    3. MongoDB
    4. Couchbase
    5. InfluxDB
    6. TimescaleDB
    7. SQLite
    8. Redis
    9. RedisJSON
    10. RedisGraph
    11. Apache Kafka
    12. RabbitMQ

    AI recommended 12 alternatives but never named mnemox-ai/tradememory-protocol. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for ensuring regulatory compliance and auditability in algorithmic trading systems?
    you: not recommended
    AI recommended (in order):
    1. Symphony
    2. OpenGamma Platform
    3. Adenza
    4. Murex MX.3
    5. Refinitiv
    6. Nice Actimize
    7. Elastic Stack

    AI recommended 7 alternatives but never named mnemox-ai/tradememory-protocol. 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 mnemox-ai/tradememory-protocol?
    pass
    AI named mnemox-ai/tradememory-protocol explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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