A side-by-side look at the Littlejohn MCP and Tradememory Protocol MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Littlejohn MCP for finance & fintech work as a local process; choose Tradememory Protocol for finance & fintech as a local process. You can also run both side by side in one mcpServers block.
LITTLEJOHN_MCP_RPC_URL, LITTLEJOHN_MCP_DATA_DIR, LITTLEJOHN_MCP_WALLETCONNECT_PROJECT_ID.get_strategy_performance, get_trade_reflection, remember_trade.Rows where the two servers differ are marked.
| Spec | L Littlejohn MCP | |
|---|---|---|
| Category | Finance & Fintech | Finance & Fintech |
| Quality signal | 39/100 · Fair | 68/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | No auth required |
| Pricing | Free | Free |
| Required env vars | LITTLEJOHN_MCP_RPC_URLLITTLEJOHN_MCP_DATA_DIRLITTLEJOHN_MCP_WALLETCONNECT_PROJECT_ID | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 1,425 |
| Directory activity | 0 views 0 installs 0 upvotes | 4 views 0 installs 0 upvotes |
| Tools | Not listed | 20 |
| Full listing | View Littlejohn MCP | View Tradememory Protocol |
No tool names declared yet. Check the project README from the listing page.
get_strategy_performanceGet aggregate performance stats per strategy.
Use this to evaluate which strategies are working and which need adjustment.get_trade_reflectionGet the full context and reflection for a specific trade.
Use this to deep-dive into a particular trade's reasoning and lessons.remember_tradeStore 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_memoriesRecall 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_analysisGet behavioral analysis from procedural memory.
Returns aggregate trading behavior stats: hold times, disposition ratio,
lot sizing variance, and Kelly criterion comparison.get_agent_stateGet 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_planCreate 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_plansCheck 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_dataFetch 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_patternsDiscover 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_backtestBacktest 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_strategyRun 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.Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
{
"mcpServers": {
"littlejohn-mcp": {
"command": "npx",
"args": [
"-y",
"@zktx.io/littlejohn-mcp"
],
"env": {
"LITTLEJOHN_MCP_RPC_URL": "YOUR_LITTLEJOHN_MCP_RPC_URL_HERE",
"LITTLEJOHN_MCP_DATA_DIR": "YOUR_LITTLEJOHN_MCP_DATA_DIR_HERE",
"LITTLEJOHN_MCP_WALLETCONNECT_PROJECT_ID": "YOUR_LITTLEJOHN_MCP_WALLETCONNECT_PROJECT_ID_HERE"
}
}
}
}
{
"mcpServers": {
"mnemox-ai-tradememory-protocol": {
"command": "uvx",
"args": [
"tradememory-protocol"
]
}
}
}