Trading Signal Analysis by Apoth3osis

Name: Trading Signal Analysis
Brand: Apoth3osis
SKU: 69858a63269243768b447d69
Price: 0.06 USD
Availability: InStock

Trading Signal Analysis

Function

Available ActionsEach successful request consumes credits as outlined below.

analyze_signals^6crbacktest_strategy^6crfull_analysis^6cr

Details

Analyze any stock or cryptocurrency with professional-grade trading signal diagnostics powered by multi-indicator technical analysis. Feed in OHLCV price data and get back actionable buy and sell signals, strategy backtests with historical performance metrics, and detailed risk analytics including maximum adverse excursion, maximum favorable excursion, win rate, expectancy, and drawdown analysis. Identify trend and momentum regimes, evaluate signal strength across multiple timeframes, and export publication-ready analysis charts and trade logs. Perfect for systematic traders building quantitative strategies, portfolio managers evaluating entry and exit timing, crypto analysts screening for momentum setups, and researchers backtesting technical indicators against real market data.

Use Cases

Generate buy and sell trading signals from technical indicators, Backtest trading strategies against historical OHLCV price data, Analyze maximum adverse excursion and maximum favorable excursion for trade risk, Calculate win rate and expectancy for systematic trading strategies, Measure portfolio drawdown and volatility metrics, Detect momentum and trend regime changes in stock or crypto markets, Export candlestick signal charts with indicator overlays, Generate trade logs for strategy performance review, Screen stocks and cryptocurrencies for technical signal setups, Evaluate entry and exit timing with multi-indicator analysis

Dynamic MCP Setup

Connect once through AgentPMT Dynamic MCP, then use approved tools from the same agent connection.

30 Second Setup

STDIO connector for Claude Code, Codex, Cursor, Zed, and other LLMs that require STDIO or custom connections.

npm install -g @agentpmt/mcp-routeragentpmt-setup

Hosted Streamable HTTPS

MCP endpoint for browser-based apps like ChatGPT, Claude, Grok, or any time you want a streamable connection with no local install.

https://api.agentpmt.com/mcp

Config Example

Use the hosted endpoint directly in clients that support remote MCP. Store your Bearer token in the client config or secret field.

Full connection guide

{
  "mcpServers": {
    "agentpmt": {
      "type": "streamable-http",
      "url": "https://api.agentpmt.com/mcp",
      "headers": {
        "Authorization": "Bearer <AGENTPMT_BEARER_TOKEN>",
        "x-instance-metadata": "{\"client\":\"generic-mcp\",\"platform\":\"remote\"}"
      }
    }
  }
}

Need client videos, organization controls, audit details, and the full feature overview?

More About Dynamic MCP

Actions(3)

analyze_signals^6cr18 params(1 required)

Detect trading signals from OHLCV data using SMA/EMA crossovers, RSI, MACD, Bollinger Bands, breakouts, and volume spikes. Returns signal counts, recent events, and latest indicator values.

candlesrequiredarray

OHLCV candle series (minimum 30 rows). Each item needs open, high, low, close (required) and optional timestamp and volume.

Array of: object

symbolstring

Optional symbol label (e.g., BTC-USD).

timeframestring

Optional timeframe label (e.g., 1H, 1D).

sma_fastinteger

SMA fast period.

Default: 20

sma_slowinteger

SMA slow period.

Default: 50

ema_fastinteger

EMA fast period.

Default: 12

ema_slowinteger

EMA slow period.

Default: 26

rsi_periodinteger

RSI period.

Default: 14

macd_signal_periodinteger

MACD signal line period.

Default: 9

bollinger_periodinteger

Bollinger Bands period.

Default: 20

bollinger_stddevnumber

Bollinger Bands standard deviation multiplier.

Default: 2

atr_periodinteger

ATR period.

Default: 14

breakout_lookbackinteger

Breakout lookback period.

Default: 20

volume_windowinteger

Volume SMA window.

Default: 20

rsi_oversoldnumber

RSI oversold threshold.

Default: 30

rsi_overboughtnumber

RSI overbought threshold.

Default: 70

volume_spike_multipliernumber

Volume spike detection multiplier.

Default: 1.5

return_indicator_seriesboolean

Return full indicator arrays in response.

backtest_strategy^6cr25 params(1 required)

Backtest a trading strategy on OHLCV data. Returns trade log, equity curve, and performance metrics (win rate, Sharpe, Sortino, drawdown, MAE/MFE).

candlesrequiredarray

OHLCV candle series (minimum 30 rows).

Array of: object

symbolstring

Optional symbol label.

timeframestring

Optional timeframe label.

strategystring

Backtest strategy to use.

Values:

sma_crossema_crossmacd_crossrsi_reversionbreakoutcomposite

Default: composite

include_shortboolean

Allow short entries.

initial_capitalnumber

Starting equity.

Default: 10000

transaction_cost_bpsnumber

Round-trip transaction cost in basis points per side.

Default: 5

max_tradesinteger

Maximum number of closed trades.

Default: 1000

sma_fastinteger

SMA fast period.

Default: 20

sma_slowinteger

SMA slow period.

Default: 50

ema_fastinteger

EMA fast period.

Default: 12

ema_slowinteger

EMA slow period.

Default: 26

rsi_periodinteger

RSI period.

Default: 14

macd_signal_periodinteger

MACD signal line period.

Default: 9

bollinger_periodinteger

Bollinger Bands period.

Default: 20

bollinger_stddevnumber

Bollinger Bands standard deviation.

Default: 2

atr_periodinteger

ATR period.

Default: 14

breakout_lookbackinteger

Breakout lookback period.

Default: 20

volume_windowinteger

Volume SMA window.

Default: 20

rsi_oversoldnumber

RSI oversold threshold.

Default: 30

rsi_overboughtnumber

RSI overbought threshold.

Default: 70

stop_loss_pctnumber

Stop loss percentage (0.001 to 0.95).

take_profit_pctnumber

Take profit percentage (0.001 to 5.0).

trailing_stop_pctnumber

Trailing stop percentage (0.001 to 0.95).

periods_per_yearinteger

Annualization factor for Sharpe/Sortino (252 for daily, 8760 for hourly).

Default: 252

full_analysis^6cr32 params(1 required)

Run both signal analysis and strategy backtest, generate downloadable charts and trade log CSV.

candlesrequiredarray

OHLCV candle series (minimum 30 rows).

Array of: object

symbolstring

Optional symbol label.

timeframestring

Optional timeframe label.

strategystring

Backtest strategy to use.

Values:

sma_crossema_crossmacd_crossrsi_reversionbreakoutcomposite

Default: composite

include_shortboolean

Allow short entries.

initial_capitalnumber

Starting equity.

Default: 10000

transaction_cost_bpsnumber

Transaction cost in basis points.

Default: 5

max_tradesinteger

Maximum closed trades.

Default: 1000

sma_fastinteger

SMA fast period.

Default: 20

sma_slowinteger

SMA slow period.

Default: 50

ema_fastinteger

EMA fast period.

Default: 12

ema_slowinteger

EMA slow period.

Default: 26

rsi_periodinteger

RSI period.

Default: 14

macd_signal_periodinteger

MACD signal line period.

Default: 9

bollinger_periodinteger

Bollinger Bands period.

Default: 20

bollinger_stddevnumber

Bollinger Bands standard deviation.

Default: 2

atr_periodinteger

ATR period.

Default: 14

breakout_lookbackinteger

Breakout lookback.

Default: 20

volume_windowinteger

Volume SMA window.

Default: 20

rsi_oversoldnumber

RSI oversold threshold.

Default: 30

rsi_overboughtnumber

RSI overbought threshold.

Default: 70

volume_spike_multipliernumber

Volume spike multiplier.

Default: 1.5

stop_loss_pctnumber

Stop loss percentage.

take_profit_pctnumber

Take profit percentage.

trailing_stop_pctnumber

Trailing stop percentage.

return_indicator_seriesboolean

Return full indicator arrays.

store_chartsboolean

Generate and store signal and performance charts.

Default: true

store_trade_logboolean

Store trade log as downloadable CSV.

Default: true

expiration_daysinteger

Cloud file retention in days (1-7).

Default: 7

chart_widthinteger

Chart width in pixels.

Default: 1400

chart_heightinteger

Chart height in pixels.

Default: 900

periods_per_yearinteger

Annualization factor for Sharpe/Sortino.

Default: 252

curl -X POST "https://api.agentpmt.com/products/purchase" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ********" \
  -d '{
    "product_id": "69858a63269243768b447d69",
    "parameters": {
      "action": "analyze_signals",
      "candles": [],
      "sma_fast": 20,
      "sma_slow": 50,
      "ema_fast": 12,
      "ema_slow": 26,
      "rsi_period": 14,
      "macd_signal_period": 9,
      "bollinger_period": 20,
      "bollinger_stddev": 2,
      "atr_period": 14,
      "breakout_lookback": 20,
      "volume_window": 20,
      "rsi_oversold": 30,
      "rsi_overbought": 70,
      "volume_spike_multiplier": 1.5
    }
  }'

import requests
import json

url = "https://api.agentpmt.com/products/purchase"

headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer ********"
}

data = {
    "product_id": "69858a63269243768b447d69",
    "parameters": {
        "action": "analyze_signals",
        "candles": [],
        "sma_fast": 20,
        "sma_slow": 50,
        "ema_fast": 12,
        "ema_slow": 26,
        "rsi_period": 14,
        "macd_signal_period": 9,
        "bollinger_period": 20,
        "bollinger_stddev": 2,
        "atr_period": 14,
        "breakout_lookback": 20,
        "volume_window": 20,
        "rsi_oversold": 30,
        "rsi_overbought": 70,
        "volume_spike_multiplier": 1.5
    }
}

response = requests.post(url, headers=headers, json=data)
print(response.status_code)
print(response.json())

const url = "https://api.agentpmt.com/products/purchase";

const headers = {
  "Content-Type": "application/json",
  "Authorization": "Bearer ********"
};

const data = {
  product_id: "69858a63269243768b447d69",
  parameters: {
    "action": "analyze_signals",
    "candles": [],
    "sma_fast": 20,
    "sma_slow": 50,
    "ema_fast": 12,
    "ema_slow": 26,
    "rsi_period": 14,
    "macd_signal_period": 9,
    "bollinger_period": 20,
    "bollinger_stddev": 2,
    "atr_period": 14,
    "breakout_lookback": 20,
    "volume_window": 20,
    "rsi_oversold": 30,
    "rsi_overbought": 70,
    "volume_spike_multiplier": 1.5
  }
};

fetch(url, {
  method: "POST",
  headers,
  body: JSON.stringify(data)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error("Error:", error));

const axios = require('axios');

const url = "https://api.agentpmt.com/products/purchase";

const headers = {
  "Content-Type": "application/json",
  "Authorization": "Bearer ********"
};

const data = {
  product_id: "69858a63269243768b447d69",
  parameters: {
    "action": "analyze_signals",
    "candles": [],
    "sma_fast": 20,
    "sma_slow": 50,
    "ema_fast": 12,
    "ema_slow": 26,
    "rsi_period": 14,
    "macd_signal_period": 9,
    "bollinger_period": 20,
    "bollinger_stddev": 2,
    "atr_period": 14,
    "breakout_lookback": 20,
    "volume_window": 20,
    "rsi_oversold": 30,
    "rsi_overbought": 70,
    "volume_spike_multiplier": 1.5
  }
};

axios.post(url, data, { headers })
  .then(response => {
    console.log(response.status);
    console.log(response.data);
  })
  .catch(error => {
    console.error("Error:", error.message);
  });

Login to view your API and budget keys. The example above uses placeholder values. Sign in to see personalized code with your bearer token.

Usage Instructions

Usage guidance provided directly by the developer for this product.

Trading Signal Analysis

Advanced signal detection, backtesting, and risk analytics engine for stock and crypto OHLCV data. Computes technical indicators, detects trading signals, runs strategy backtests with MAE/MFE analysis, and generates downloadable charts and trade logs.

Actions

analyze_signals

Detect trading signals from OHLCV candle data. Computes SMA, EMA, RSI, MACD, Bollinger Bands, ATR, breakout levels, and volume analysis. Returns signal counts, recent signal events, and current indicator values.

Required: candles (array of OHLCV objects, minimum 30 rows)

{
  "candles": [
    {"timestamp": "2024-01-01T00:00:00Z", "open": 42000, "high": 42500, "low": 41800, "close": 42300, "volume": 1500},
    {"timestamp": "2024-01-02T00:00:00Z", "open": 42300, "high": 43000, "low": 42100, "close": 42800, "volume": 1800}
  ],
  "symbol": "BTC-USD",
  "timeframe": "1D"
}

backtest_strategy

Run a strategy backtest on OHLCV data. Returns trade log, equity curve, and metrics (win rate, Sharpe, Sortino, max drawdown, MAE/MFE, profit factor).

Required: candles

{
  "candles": [{"open": 100, "high": 105, "low": 98, "close": 103, "volume": 5000}],
  "symbol": "AAPL",
  "strategy": "sma_cross",
  "initial_capital": 10000,
  "stop_loss_pct": 0.02,
  "take_profit_pct": 0.05
}

full_analysis

Run both signal analysis and backtest, generate downloadable signal chart, performance chart, and trade log CSV.

Required: candles

{
  "candles": [{"open": 100, "high": 105, "low": 98, "close": 103, "volume": 5000}],
  "symbol": "ETH-USD",
  "timeframe": "1H",
  "strategy": "composite",
  "initial_capital": 50000,
  "store_charts": true,
  "store_trade_log": true
}

Candle Data Format

Each candle object requires:

open (number) -- Open price (required)
high (number) -- High price (required)
low (number) -- Low price (required)
close (number) -- Close price (required)
timestamp (string) -- Optional timestamp
volume (number) -- Optional volume (defaults to 0)

Minimum 30 candles required; more is better for accurate indicator calculations.

Strategy Options

Strategy	Description
sma_cross	SMA fast/slow crossover
ema_cross	EMA fast/slow crossover
macd_cross	MACD line/signal crossover
rsi_reversion	Mean reversion on RSI oversold/overbought
breakout	Price breakout above/below rolling high/low
composite	Multi-indicator consensus (default, requires 3+ aligned signals)

Indicator Parameters

All have sensible defaults. Key ones:

sma_fast / sma_slow -- SMA periods (default: 20/50)
ema_fast / ema_slow -- EMA periods (default: 12/26)
rsi_period -- RSI period (default: 14)
macd_signal_period -- MACD signal period (default: 9)
bollinger_period / bollinger_stddev -- Bollinger Bands (default: 20/2.0)
atr_period -- ATR period (default: 14)
breakout_lookback -- Rolling high/low window (default: 20)

Risk Controls

stop_loss_pct -- Stop loss as decimal (e.g., 0.02 = 2%)
take_profit_pct -- Take profit as decimal (e.g., 0.05 = 5%)
trailing_stop_pct -- Trailing stop as decimal

Output Options

return_indicator_series -- Include full indicator arrays (default: false)
store_charts -- Generate PNG charts (default: true, full_analysis only)
store_trade_log -- Generate CSV trade log (default: true, full_analysis only)
expiration_days -- File retention 1-7 days (default: 7)
chart_width / chart_height -- Chart dimensions in pixels

Performance Metrics

Backtest results include:

total_trades, wins, losses, win_rate_pct
total_return_pct, final_equity
max_drawdown_pct
expectancy_pct -- Average trade return
profit_factor -- Sum of wins / sum of losses
sharpe -- Annualized Sharpe ratio
sortino -- Annualized Sortino ratio
average_trade_mae_pct -- Average Maximum Adverse Excursion
average_trade_mfe_pct -- Average Maximum Favorable Excursion
average_bars_held -- Average trade duration

Important Notes

Candle data must have at least 30 rows; more rows than the largest indicator window + 2.
sma_fast must be less than sma_slow; ema_fast must be less than ema_slow.
rsi_oversold must be less than rsi_overbought.
Transaction costs are applied as basis points per side (default 5 bps = 0.05%).
Set periods_per_year to match your data frequency (252 for daily, 8760 for hourly).
Charts are stored in cloud storage with signed download URLs.

Frequently Asked Questions

How do I connect this tool to an external agent?

You can install the local MCP server by opening a terminal and running:

Install commands

npm install -g @agentpmt/mcp-router
agentpmt-setup

This will connect you to local agents like Claude Code, Windsurf, Grok Build, Cursor, etc.

Alternatively you can connect to the hosted version with this config block, no installation required:

Hosted MCP config

{
  "mcpServers": {
    "agentpmt": {
      "type": "streamable-http",
      "url": "https://api.agentpmt.com/mcp",
      "headers": {
        "Authorization": "Bearer <AGENTPMT_BEARER_TOKEN>",
        "x-instance-metadata": "{\"client\":\"generic-mcp\",\"platform\":\"remote\"}"
      }
    }
  }
}

View MCP Connection Instructions for more details.

How does an external agent use this tool?

After the external agent is connected to an Agent Group that can use this tool, paste this prompt into the agent:

Agent prompt

Use the AgentPMT-Tool-Search-and-Execution tool. First call action 'get_instructions' so you know how to use the tool search interface. Then call action 'get_schema' with tool_id 69858a63269243768b447d69 ("Trading Signal Analysis"). After reading the schema and any returned instructions, tell me what this tool can do, we are going to be using it

The agent should fetch the tool schema first, collect the required parameters for your request, and then call the tool through AgentPMT.

Trading Signal Analysis

Available ActionsEach successful request consumes credits as outlined below.

Details

Use Cases

Dynamic MCP Setup

30 Second Setup

Hosted Streamable HTTPS

Config Example

Actions(3)

Credit-Based Access Using AgentAddress

Direct x402 Payment

Usage Instructions

Trading Signal Analysis

Actions

analyze_signals

backtest_strategy

full_analysis

Candle Data Format

Strategy Options

Indicator Parameters

Risk Controls

Output Options

Performance Metrics

Important Notes

Frequently Asked Questions

How do I connect this tool to an external agent?

How does an external agent use this tool?

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