The Zero-Friction AI Copilot for Binance: Bridge the gap between Freqtrade/CCXT power and IDE-native AI Agents. Provides MCP tools for Binance trading, market analysis, diagnostics, and bot scaffolding.
Server has 13 tools with complete schemas and descriptions, but quality is inconsistent. Naming follows verb_noun convention well (get_ticker, execute_live_order, simulate_order). Descriptions range 50-250 chars, meeting baseline. However, critical gaps: (1) parameter descriptions are sparse or missing context (e.g., 'testPrice' in inspect_symbol_filters lacks units/range); (2) output schemas are not documented, LLMs cannot plan downstream calls; (3) error handling is generic, no recovery guidance; (4) high-risk tools (execute_live_order) lack confirmation patterns despite IRREVERSIBLE risk classification. Tool composition is reasonable but some tools combine concerns (simulate_order handles TRADE/GET_PORTFOLIO/RESET as one tool).
Calculate optimal position size, risk-reward ratio, and Kelly Criterion sizing based on account balance, entry/exit prices, and strategy win rate.
Check current API rate limit weight usage and get recommendations to avoid HTTP 429/418 IP bans.
Convert trading strategies from PineScript, Freqtrade, or natural language descriptions into executable TypeScript or Python code.
Diagnose HMAC-SHA256 signature generation issues and validate query string serialization for Binance API requests.
Execute a real live order on Binance Spot market with mandatory confirmation flag, slippage checks, and circuit breaker safety limits.
Explain Binance error codes with common causes and recommended fixes in TypeScript, Python, and CCXT.
Fetch current and historical funding rates for Binance USD-M Futures contracts to assess leverage trading costs.
Output schemas not documented. LLMs cannot infer what fields are returned, blocking downstream tool chaining and forcing discovery calls.
Parameter descriptions lack units, ranges, and constraints. E.g., 'testPrice' in inspect_symbol_filters has no units; 'limit' in get_klines_analysis defaults to 100 but no min/max stated.
execute_live_order is IRREVERSIBLE but lacks dry-run or multi-step confirmation. isConfirmed flag is present but no guidance on how LLM should obtain user approval before calling.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 49 | <=2025-11-25 | v2 |
Fetch and analyze candlestick data (OHLCV) with technical indicators (SMA, RSI, MACD, Bollinger Bands) for a symbol and timeframe.
Analyze order book depth and calculate buy/sell imbalance ratio to detect market sentiment and potential price moves.
Fetch real-time ticker data (24h price, volume, bid/ask) for a trading pair from Binance Spot or Futures market.
Inspect trading filters and constraints for a Binance symbol to validate order parameters against tickSize, stepSize, minQty, and minNotional rules.
Generate boilerplate trading bot code for Grid Trading, DCA Martingale, or RSI Reversal strategies in TypeScript, Python, or CCXT async.
Simulate order execution in a virtual paper trading environment with realistic fee calculations, position tracking, and portfolio performance metrics.
simulate_order combines three unrelated actions (TRADE, GET_PORTFOLIO, RESET) into one tool. Should split into separate tools: execute_simulated_trade, get_paper_portfolio, reset_paper_trading.
Error handling is generic. No recovery guidance in descriptions. E.g., 'Binance API error' tells LLM nothing about retry eligibility or next steps.