AgentIndex icon
AgentIndex
ToolsCategoriesTrendingNewCompare
Submit Tool
ToolsCategoriesTrendingNewCompare
Home/
Memory & Context/
tradememory-protocol
tradememory-protocol logo

tradememory-protocol

Active·★ 1.3k·MIT·Updated 2026-06-01
★ Memory & Context★ Multi-Agent

TradeMemory Protocol provides a persistent memory layer for trading agents, enabling them to recall past trades with context, discover patterns, and evolve strategies autonomously. It features outcome-weighted recall, cognitive memory architecture, and an evolution engine for strategy discovery. Available as an MCP server for integration with Claude and other agents.

tradememory-protocol is currently grouped under Memory & Context, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Persistent memory with full context for every trade and Crypto trading: Feed BTC/ETH trades and discover timing patterns automatically. The listed license is MIT, which is useful when adoption constraints matter. It also shows measurable community traction with 1.3k GitHub stars.

#ai-agents#claude#crypto#evolution-engine#forex#mcp#mcp-server#mcp-servers
$ Install
$ pip install tradememory-protocol
↗ Visit site★ GitHub
01

Features

01Persistent memory with full context for every trade
02Outcome-weighted recall (OWM) for adaptive learning
03Evolution Engine for autonomous strategy discovery
0415 MCP tools for memory, cognitive, and evolution operations
05Multi-platform support (crypto, forex, MT5, etc.)
02

Why choose it

+Persistent memory with full context for every trade
+Crypto trading: Feed BTC/ETH trades and discover timing patterns automatically
+Covers 4 supported environments or platforms, which is helpful for broader deployment needs.
+Ships with a public repository and a MIT license, which makes adoption and review easier.
03

Trade-offs

!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.
04

Compatibility

Claude Desktop
MCP client
Verified via docs
Claude Code
CLI agent
Verified via docs
Python API
Python SDK
Verified via docs
Docker
Container
Verified via docs
05

Quick start

1
$ pip install tradememory-protocol
06

Use cases

↳Crypto trading: Feed BTC/ETH trades and discover timing patterns automatically
↳Forex + MT5: Auto-sync trades and leverage persistent memory for adaptive strategies
↳Developers: Build memory-aware trading agents with 15 MCP tools and 30+ REST endpoints
07

How it compares

≈tradememory-protocol sits in the Memory & Context category, so it makes more sense to evaluate it alongside tools like letta instead of in isolation.
≈If your main need is closer to "Crypto trading: Feed BTC/ETH trades and discover timing patterns automatically", that use case is a better lens for comparison than broad feature checklists alone.
≈tradememory-protocol uses a MIT license, and community traction are both easier to judge in category context.
08

Alternatives

letta logo
letta★ 23.4k
Letta is the platform for building stateful agents: open AI with advanced memory that can learn and self-improve over time.
vs →
DesktopCommanderMCP logo
DesktopCommanderMCP★ 6.2k
This is MCP server for Claude that gives it terminal control, file system search and diff file editing capabilities
vs →
fastmcp logo
fastmcp★ 25.7k
🚀 The fast, Pythonic way to build MCP servers and clients.
vs →
FunASR logo
FunASR★ 18.2k
Industrial-grade speech recognition toolkit: 170x realtime, 50+ languages, speaker diarization, emotion detection, streaming, and OpenAI-compatible API.
vs →
nuclear logo
nuclear★ 17.8k
Streaming music player that finds free music for you
vs →
Auto-claude-code-research-in-sleep logo
Auto-claude-code-research-in-sleep★ 12.3k
ARIS ⚔️ (Auto-Research-In-Sleep) — Claude Code skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation via Codex MCP
vs →
agents-best-practices logo
agents-best-practices★ 2.0k
Provider-neutral Agent Skill for Codex, Claude Code, and agentic harness design.
vs →
holaOS logo
holaOS★ 5.5k
The agent environment for long-horizon work, continuity, and self-evolution.
vs →
See all alternatives →

Related searches

tradememory-protocol AlternativesBest Memory & Context Tools 2026Open Source Memory & Contexttradememory-protocol Tutorialtradememory-protocol Vs Competitorsai-agentsclaudecrypto

Comments

Log in to leave a comment
  • yang xiao
    yang xiaoMay 26, 2026

    Interesting concept — giving trading agents persistent memory is a game changer for strategy continuity. Still early but the protocol design looks solid.

  • oneday
    onedayMay 25, 2026

    文档有点薄，需要自己看源码才能搞清楚 memory schema 怎么定义。不过核心思路是对的，持久化交易记忆确实是 Agent 交易系统缺的一环。

On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07How it compares08Alternatives
Stats
GitHub Stars★ 1.3k
Last commit2w ago
StatusActive
LicenseMIT
CategoryMemory & Context
Trend (30d)
+0k↑ 1.0%
Links
Documentation↗Discussion↗Issues↗Releases↗

Deploy on DigitalOcean — Get $200 Free Credit

Ad
© 2026 AgentIndex.app|Built by a 10-year iOS Developer.
QYSGitHubBuy me a coffee ☕

Browse by Category

Code AssistantWorkflow AutomationRAG / Knowledge BaseMulti-AgentBrowser AutomationLLM InfraDev ToolingObservability

Not affiliated with Anthropic, OpenAI or Microsoft.