MCP.Market

Tradememory Protocol MCP server

by mnemox-ai·io.github.mnemox-ai/tradememory-protocol·v0.5.6·1.4k stars
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Tamper-evident decision audit trail and outcome-weighted memory for AI trading agents.

B83/100grade B
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Safety scan
B83/100

full report

Adoption
Established

1.4k stars125 downloads/wk

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If you have run it, two minutes of your experience saves the next person an afternoon.

Tradememory Protocol tools (22, 4 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • brake_status

    What the brake in front of this broker will and will not let through.

  • check_active_plans

    Check active trading plans against current market context.

  • check_trade_legitimacy

    Check if the agent has sufficient data and confidence to trade.

  • compute_dqs

    Compute Decision Quality Score before executing a trade.

  • create_trading_planwrite action

    Create a prospective trading plan that activates when conditions are met.

  • evaluate_orderwrite action

    Ask the brake what it would do with this order, without placing it.

  • evolution_discover_patterns

    Discover trading patterns from market data using LLM analysis.

  • evolution_evolve_strategywrite action

    Run full evolution loop — generate, backtest, select, eliminate.

  • evolution_fetch_market_data

    Fetch OHLCV market data from Binance for evolution analysis.

  • evolution_get_log

    Get the log of past evolution runs from this session.

  • evolution_run_backtestwrite action

    Backtest a candidate pattern against historical OHLCV data.

  • export_audit_trail

    Export Trading Decision Records for audit and compliance review.

  • get_agent_state

    Get the current agent affective state (confidence, risk, drawdown).

  • get_behavioral_analysis

    Get behavioral analysis from procedural memory.

  • get_daily_root

    Get (or rebuild) the daily Merkle root for a UTC date.

  • get_strategy_performance

    Get aggregate performance stats per strategy.

  • get_trade_reflection

    Get the full context and reflection for a specific trade.

  • recall_memories

    Recall memories using OWM outcome-weighted scoring.

  • remember_trade

    Store a trade into OWM multi-layer memory with automatic updates.

  • validate_strategy

    Validate a trading strategy using statistical tests (DSR + Walk-Forward + Regime + CPCV).

  • verify_audit_chain

    Verify the integrity of the audit chain.

  • verify_audit_hash

    Verify the integrity of a Trading Decision Record.

Public scan report

scanner v0.1.10 · 2026-10-15 · same rubric, same numbers if you re-run it

1 medium
  • Code scan116 source files scanned20/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 6 days ago15/15
  • Maintainer identityregistry namespace matches repository owner7/10

Findings (1)

  • mediumsubprocess with shell=Trueexec.shell-true
    tradememory_protocol-0.5.6/src/tradememory/onboarding/setup_wizard.py: …_install_cmd"], shell=True, capture_output…
Overall 83/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How Tradememory Protocol compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
83/100
higher than 65% of 48,255 servers
Tools
22
the typical server has 7
Tools that change things
18%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
1,430
more than 95% of 28,688 servers
Downloads a week
125
more than 67% of 12,191 servers with a package

What its tools let an agent do: 18 read · 1 create · 2 change · 1 run or deploy

Release history: 2 versions in the registry since 2026-09-08, latest 2026-10-02, typically one every 24 days.

Install Tradememory Protocol in Claude Code, Cursor or VS Code

claude mcp add tradememory-protocol -- uvx tradememory-protocol
Add to Cursor

What the publisher says

From the Tradememory Protocol repository's README, as published. We do not edit it. Read it on GitHub

<!-- mcp-name: io.github.mnemox-ai/tradememory-protocol -->

Getting Started | Use Cases | API Reference | OWM Framework | Limitations | 中文版

Project status (August 2026): Feature-complete, in maintenance mode — bug and security reports are still reviewed; no new features or hosted service are planned. For paid work, see Trading Record Analysis.

Your trading AI has amnesia. And regulators are starting to notice.

It makes the same mistakes every session. It can't explain why it traded. It forgets everything when the context window ends. Meanwhile, MiFID II is raising the bar for algorithmic decision documentation (Article 17). The EU AI Act demands systematic logging of AI actions (Article 14). Your competitors' agents are learning from every trade.

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 a SHA-256 tamper-evident audit trail.

Used by an independent trader running a pre-flight checklist before every position, and first-party against an MT5 account that logs blocked signals as well as executed ones. See USE_CASES.md for which is which.

What it does

  • Before trading: ask your memory — what happened last time in this market condition? How did it end?
  • After trading: one call records everything — five memory layers update automatically
  • Safety rails: confidence tracking, drawdown alerts, losing streak detection — the system tells you when to stop

Works with any market (stocks, forex, crypto, futures), any broker, any AI platform. TradeMemory doesn't execute trades or touch your money — it only records and recalls.

See the interface

tradememory-dashboard.onrender.com — the dashboard running on an illustrative demo dataset. Nothing to install.

It is an interface preview, not a track record: the trades are synthetic and every figure on it is labelled as such. For what the memory layer actually does in a terminal, pip install tradememory-protocol && tradememory demo --fast replays 30 trades and shows the recall and parameter adjustment it derives from them.

Quick Start

pip install tradememory-protocol

Add to Claude Desktop (claudedesktopconfig.json):

{
  "mcpServers": {
    "tradememory": {
      "command": "uvx",
      "args": ["tradememory-protocol"]
    }
  }
}

Then tell Claude: "Record my AAPL long at $195 — earnings beat, institutional buying, high confidence."

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

Tradememory Protocol: common questions

Is Tradememory Protocol MCP server safe?
Mostly: it is graded B (83/100). Read the Tradememory Protocol safety report
How do I install Tradememory Protocol?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does Tradememory Protocol need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is Tradememory Protocol maintained?
The last commit was 25 days ago (2026-10-09). The latest release is v0.5.6.
What can I use instead of Tradememory Protocol?
Servers from other publishers that do the same job: SSH Manager MCP server and State Memory MCP server.
How does Tradememory Protocol compare with other MCP servers?
safety score 83/100 (higher than 65% of 48,255 servers); tools 22 (the typical server has 7); tools that change things 18% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

Alternatives to Tradememory Protocol

Same job from other publishers: the closest match first, then the best rated.

  • SSH Manager
    SSH for AI agents: commands, files, backups and health, with approval, a vault and an audit trail
    A
  • State Memory MCP
    Persistent workflow graph server tracking tasks, decisions, spatial entities, and blockers.
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