mnemox-ai/tradememory-protocol
Decision audit trail + persistent memory for AI trading agents. Outcome-weighted recall, tamper-evident SHA-256 chain with RFC 3161 anchoring, 20 MCP tools. observed · 2026-08-28
Health v2 · maintenance only
80/100
- Activity 97
- Release rhythm 95
- Longevity 13
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 2
- age_days: 191
- days_rel: 36
- days_push: 22
- n_releases_24m: 10
Adoption not part of the score
1412 stars · 166 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
TradeMemory Protocol is an MCP server providing persistent memory and a tamper-evident decision audit trail for AI trading agents, with outcome-weighted recall across five memory layers and 20 MCP tools. It records trades with SHA-256 chaining and RFC 3161 timestamp anchoring to support MiFID II and EU AI Act compliance, without executing trades itself.
Use cases
- give my AI trading agent persistent memory across sessions
- recall past trades in similar market conditions before entering a position
- create a tamper-evident audit trail of AI trading decisions for regulators
- track drawdown and losing streaks to know when to stop trading
- log MT5 or forex expert advisor decisions automatically
- review strategy decay and behavioral drift in daily trading reflections
When to choose
- you run AI agents (e.g., Claude) that trade and need cross-session memory of trades and outcomes
- you need regulator-ready, tamper-evident decision documentation for algorithmic trading
- you want pre-flight recall of similar past trades before opening positions
- you use MCP-compatible AI platforms and want a pip-installable memory layer
When to avoid
- you need order execution or broker integration - it deliberately does not trade
- you expect new features or a hosted service - the project is in maintenance mode
- you need a general-purpose agent memory system unrelated to trading
- you require real-time low-latency trade execution support rather than post-trade logging
Facets
service · maturity maintenance
mcp logging monitoring security fintech large-language-models legal developer-tools python self-hosted cross-platform mcp-server trading-journal tamper-evident outcome-weighted-memory miifid-ii eu-ai-act sha-256-chain rfc-3161 forex crypto mt5 claude audit-trail memory trading ai-agents
4 sources
- readme: https://github.com/mnemox-ai/tradememory-protocol · fetched 2026-08-28 · 2d2737412715
- homepage: https://mnemox.ai/tradememory/ · fetched 2026-08-29 · 43f07a9db391
- registry_pypi: https://pypi.org/pypi/tradememory-protocol/json · fetched 2026-08-29 · c55cecd8d24a
- site_page: https://www.mnemox.ai/pricing · fetched 2026-08-29 · d8ccd66f6330
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| mnemox-ai/tradememory-protocol | main | 80 |
For agents
markdown · JSON · MCP: product_card(name="mnemox-ai/tradememory-protocol")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem