In-depth architectural comparison of the Tradememory Protocol and Signer MCP MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Tradememory Protocol
Finance & Fintech · Local stdio
Quality: 68/100 (Great) | Auth: No auth required
Signer MCP
Finance & Fintech · Local stdio
Quality: 59/100 (Good) | Auth: API Key required
Verdict Summary: Choose Tradememory Protocol if you need specialized Finance & Fintech tools running via a local process. Choose Signer MCP if your workspace requires Finance & Fintech integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Tradememory Protocol when:
You need dedicated capabilities in the Finance & Fintech domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Glama 🐍 🏠 - Structured 3-layer memory system (trades → patterns → strategy) for AI trading agents. Supports MT5, Binance, and Alpaca.
Keyless CEX/DEX signing for AI trading agents (Binance, OKX, Bybit, KuCoin, Hyperliquid, Asterdex). Signing keys never leave an AWS Nitro Enclave (attested PCR0); agents receive policy-bounded signatures, not credentials. Built to survive prompt injection and supply-chain key leaks. 5 tools, stdio. Install with npx -y @usenami/signer-mcp.
Category & Scope
Tools & Capabilities Breakdown
Tradememory Protocol Tools (20)
get_strategy_performance
Get aggregate performance stats per strategy.
Use this to evaluate which strategies are working and which need adjustment.
get_trade_reflection
Get the full context and reflection for a specific trade.
Use this to deep-dive into a particular trade's reasoning and lessons.
remember_trade
Store a trade into OWM multi-layer memory with automatic updates.
Writes to episodic memory and automatically updates semantic (Bayesian),
procedural (running averages + hold time + Kelly), and affective
(EWMA confidence/streaks). Also writes to trade_records for backward
compatibility.
recall_memories
Recall memories using OWM outcome-weighted scoring.
Queries episodic and semantic memories, scores them by outcome quality,
context similarity, recency, confidence, and affective modulation.
Returns ranked memories with score breakdown.
get_behavioral_analysis
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Tradememory Protocol is categorized under Finance & Fintech and uses a local stdio subprocess. In contrast, Signer MCP belongs to Finance & Fintech using local stdio subprocess. Select Tradememory Protocol when you need capabilities focused on finance & fintech and Signer MCP when you require tools for finance & fintech.
Get behavioral analysis from procedural memory.
Returns aggregate trading behavior stats: hold times, disposition ratio,
lot sizing variance, and Kelly criterion comparison.
get_agent_state
Get the current agent affective state (confidence, risk, drawdown).
Returns confidence level, risk appetite, drawdown percentage,
win/loss streaks, equity tracking, and a recommended action
based on current drawdown severity.
create_trading_plan
Create a prospective trading plan that activates when conditions are met.
Stores a rule-based plan in prospective memory. The plan stays active
until triggered, expired, or manually cancelled.
check_active_plans
Check active trading plans against current market context.
Queries all active prospective plans, expires any past their expiry date,
and matches remaining plans against the provided context.
evolution_fetch_market_data
Fetch OHLCV market data from Binance for evolution analysis.
Downloads historical price bars for backtesting and pattern discovery.
Use this before discover_patterns or run_backtest to get data.
evolution_discover_patterns
Discover trading patterns from market data using LLM analysis.
Uses Claude to analyze OHLCV data and generate candidate trading patterns
with entry/exit conditions. Each pattern can be backtested afterward.
evolution_run_backtest
Backtest a candidate pattern against historical OHLCV data.
Takes a pattern dict (from discover_patterns) and runs a vectorized
backtest. Returns fitness metrics: Sharpe ratio, win rate, trade count,
max drawdown, total PnL.
evolution_evolve_strategy
Run full evolution loop — generate, backtest, select, eliminate.
Multi-generation strategy evolution: generates candidate patterns via LLM,
backtests on in-sample data, validates survivors on out-of-sample data,
eliminates weak hypotheses. Returns graduated strategies and graveyard.
+8 more tools listed on main page
Signer MCP Tools (7)
list_venues
Returns the static manifest of venues this Signer can sign for. **Read-only**, does not contact the gateway, works without a token. Call this first to discover what's supported.
get_attestation
Fetches the Nitro attestation document **with a fresh nonce** and verifies it locally
get_verified_price
Reads a Uniswap V3 token price from The Graph and returns it **only if four checks pass**.
get_account
Returns equity, free margin, and open positions for a venue.
place_order
Place a single market or limit order. The enclave signs the payload after checking policy caps,
place_hedge
Places a 2-leg hedge with **atomic signing**: both legs are signed inside the
cancel_order
Cancels an outstanding order by its venue order id. Idempotent — cancelling an already-filled or non-existent order returns `ok: false` with a venue reason instead of erroring.