AI Trading Tools: Signal Analysis Live on AgentPMT

AI Trading Tools: Signal Analysis Live on AgentPMT

Most traders stare at charts all day, toggling between six indicator windows, and still miss the crossover that mattered. The signal was there -- they just ran out of screens.

What It Does

Trading Signal Analysis is a new tool on the AgentPMT marketplace, built by Apoth3osis and accessible through both the web interface and the AgentPMT MCP server. It runs professional-grade, multi-indicator technical diagnostics on any stock or cryptocurrency you feed it -- and returns structured, machine-readable results an AI agent can act on directly.

How It Works

The tool exposes three actions. The first, analyze_signals, accepts OHLCV candle data (minimum 30 rows) and runs it through SMA/EMA crossovers, RSI, MACD, Bollinger Bands, breakout detection, and volume spike analysis. You control every parameter: fast and slow periods for moving averages, RSI overbought/oversold thresholds, Bollinger standard deviation multipliers, ATR periods, and volume spike multipliers. The output includes signal counts by type, recent signal events, and current indicator values -- all in structured JSON.

The second action, backtest_strategy, takes the same candle input and simulates trades using one of six strategies: sma_cross, ema_cross, macd_cross, rsi_reversion, breakout, or a composite strategy that layers multiple signals. It returns a full trade log, equity curve, and performance metrics including win rate, Sharpe ratio, Sortino ratio, maximum drawdown, and MAE/MFE analysis. You set initial capital, transaction costs in basis points, stop-loss and take-profit percentages, and trailing stops.

The third action, full_analysis, combines both signal detection and backtesting into a single call. It also generates downloadable charts (signal overlays and performance curves) and exports the trade log as a CSV. Chart dimensions and cloud file retention (1-7 days) are configurable. Each call costs 6 credits.

What You Can Build With It

A portfolio monitoring agent that pulls daily candles for 50 tickers, runs analyze_signals on each, and flags only the ones with fresh MACD crossovers or RSI divergences -- cutting a two-hour morning screen to a two-minute summary. A crypto research agent that backtests every alt-coin in a watchlist against the composite strategy, ranks them by Sharpe ratio, and pipes the top five into a Discord channel before London open. A risk management system that monitors open positions, detects Bollinger Band squeezes and volume spikes, and triggers alerts when conditions shift.

These are workflows an AI agent handles end-to-end. The structured outputs from Trading Signal Analysis feed directly into downstream decision logic without manual parsing or screen-reading. The tool handles the quantitative analysis; the agent handles the orchestration.

Where This Fits

Across financial services, energy trading desks, and professional services firms, AI trading tools are moving from experimental side projects to core infrastructure. Algorithmic trading strategies that once required dedicated quant teams and proprietary platforms are becoming accessible through composable, pay-per-use tool APIs. Trading Signal Analysis sits at that intersection -- delivering institutional-grade technical analysis at 6 credits per call, with no subscriptions, no seat licenses, and no minimum commitments. For fintech AI applications, risk assessment pipelines, and financial automation workflows, that unit economics profile changes what is worth building.

The tool supports both traditional equities and cryptocurrency markets. Any asset with OHLCV data -- stocks, futures, forex pairs, Bitcoin, Ethereum, alt-coins -- runs through the same analytical engine. That cross-asset flexibility matters for firms operating across multiple markets or agents that need to compare opportunities across asset classes.

Try It

Trading Signal Analysis is available now on the AgentPMT marketplace. Connect it through the MCP server, pass it candle data, and get back the signals that took your last analyst three hours to compile. Six credits. Structured output. No fluff.