prop-firm-intel-mcp

Which prop firm challenge actually has positive EV for your strategy? Now you can calculate it.

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What Is This?

The prop trading firm industry has exploded to over $3 billion in annual challenge fee revenue. Retail traders spend $100–$1,500 per challenge attempt, often without any rigorous analysis of whether the challenge parameters are actually beatable given their strategy's historical performance.

prop-firm-intel-mcp gives AI assistants a structured, queryable database of 7 major prop trading firms — with complete challenge rules, pricing, payout structures, and critically, an expected value (EV) calculator that takes your win rate and risk:reward ratio as inputs and tells you mathematically which challenges you can beat.

Stop guessing. Start calculating.

This actor uses a static, manually-verified database — not live web scraping. Prop firm rules change frequently; we update the database with each verified rule change and version-stamp every dataset so you always know exactly what data you're working with.

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Firms Covered

Firm	Challenge Tiers	Profit Target	Max Drawdown	Payout Split	Starting Price
TopstepX	Futures, Express	6%	3% daily / 6% total	90%	$49/month
Apex Trader Funding	Full, Static	6%	3% daily / 6% trailing	100% (after fee)	$147 one-time
FTMO	FTMO Challenge, Swing	10%	5% daily / 10% total	80–90%	$155 one-time
MyFundedFutures	Standard, Starter	6%	2% daily / 6% trailing	90%	$49/month
E8 Markets	Standard, Straight-Through	8%	5% daily / 8% total	80%	$228 one-time
The Trading Pit	Standard	8%	5% daily / 8% total	80%	€99 one-time
Funded Trading Plus	Standard, Accelerated	10%	5% daily / 10% total	90%	$119 one-time

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Who Uses This?

User Type	Use Case	Value
Retail Traders	Choosing which challenge to attempt given their trading strategy	Mathematical EV calculation instead of guessing
Trading Coaches	Recommending prop firms to students	Objective data to support recommendations
Financial Newsletter Writers	Prop firm comparison content	Structured data for comparison tables and analysis
Quantitative Retail Traders	Backtesting-informed challenge selection	Input real backtest stats; get real EV outputs
Trading Discord/Community Moderators	Answering member questions about prop firms	Fast structured lookup without visiting 7 different websites
Social Media Trading Educators	Content creation around prop firms	Comparison data for YouTube/TikTok content
Algorithmic Retail Traders	EA/bot prop firm compatibility checking	Rule-set filtering for news trading, overnight holds, EA use

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Feature Overview

Feature	Detail
Compare Mode	Side-by-side comparison of all 7 firms on any parameter
Firm Rules Mode	Deep dive into one firm's complete rule set
Promotions Mode	Active discount codes and promotional pricing
EV Calculator	Input win rate + R:R ratio → expected value per challenge
Rule Compatibility Filter	Filter firms by: EA-allowed, news-trading-allowed, overnight-holds-allowed, weekend-holds-allowed
Payout Analysis	Calculate expected monthly payout given account size + win rate
Cost Recovery Analysis	How many winning months before your challenge fee is recovered
Risk-Adjusted ROI	EV normalized to challenge cost for cross-firm comparison
Historical Price Data	Track when firms have run promotions and how aggressive
Version-Stamped Data	Every dataset includes a verification date and change log

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The EV Calculator — How It Works

Prop firm challenges are a probabilistic event with a defined cost, a defined success probability, and a defined payout distribution. The EV calculator treats them correctly as such.

Inputs:

• winRate: Your historical win rate (0.0–1.0)
• rrRatio: Your average risk:reward ratio (e.g., 1.5 means you risk 1 to make 1.5)
• avgTradesPerDay: Your average daily trade count
• challengeDurationDays: Challenge duration in days
• challengeCost: One-time or monthly challenge cost
• accountSize: Account size being challenged for

The model calculates:

1. Expected daily P&L = winRate × rrRatio × riskPerTrade - (1 - winRate) × riskPerTrade
2. Probability of hitting profit target = Monte Carlo simulation over challengeDurationDays given your edge and daily variance
3. Probability of breaching drawdown = Same simulation, tracking drawdown path
4. Net EV per challenge attempt = P(pass) × expectedPayoutYear1 - P(fail) × challengeCost
5. Break-even win rate = The minimum win rate at which this challenge has positive EV given your R:R

Important: EV is calculated over the first 12 months of funded trading (not the challenge phase alone), because the real profit opportunity is in the payout stream, not the challenge itself.

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Quick Start

MCP Mode

{
  "mcpServers": {
    "prop-firm-intel": {
      "command": "npx",
      "args": [
        "-y",
        "@apify/mcp-client",
        "--actor-id",
        "your-username/prop-firm-intel-mcp",
        "--token",
        "YOUR_APIFY_TOKEN"
      ]
    }
  }
}

Ask Claude:

"My backtest shows a 52% win rate with 1.8 R:R ratio, trading ES futures, averaging 4 trades per day. Which prop firm challenge has the best EV for my strategy? I need to allow overnight holds."

Direct API Mode

curl -X POST https://api.apify.com/v2/acts/your-username~prop-firm-intel-mcp/run-sync \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "mode": "calculate_ev",
    "winRate": 0.52,
    "rrRatio": 1.8,
    "avgTradesPerDay": 4,
    "requireOvernightHolds": true,
    "sortBy": "netEV"
  }'

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MCP Tools Reference

compare_firms

Get a structured comparison across all 7 firms on specified parameters.

Parameters:

Parameter	Type	Required	Description
compareOn	array	No	Fields to compare: profitTarget, maxDailyDrawdown, maxTotalDrawdown, payoutSplit, price, challengeDuration, minimumTradingDays, payoutFrequency
accountSize	string	No	Filter to specific account size tier (e.g., 50000, 100000, 200000)
instrumentType	string	No	futures, forex, cfd, crypto
requireEAAllowed	boolean	No	Filter to firms that allow EAs/bots
requireOvernightHolds	boolean	No	Filter to firms allowing overnight positions
requireWeekendHolds	boolean	No	Filter to firms allowing weekend holds
requireNewsTrading	boolean	No	Filter to firms allowing news trading
sortBy	string	No	Sort results by: price, payoutSplit, profitTarget, drawdown

Response:

{
  "comparison": [
    {
      "firm": "Apex Trader Funding",
      "accountSizes": [25000, 50000, 75000, 100000, 150000, 250000, 300000],
      "selectedTier": {
        "size": 50000,
        "price": 147,
        "profitTarget": 3000,
        "profitTargetPct": 0.06,
        "maxDailyDrawdown": 1500,
        "maxTotalDrawdown": 2500,
        "drawdownType": "trailing",
        "minTradingDays": 7,
        "challengeDurationDays": "unlimited",
        "payoutSplit": 1.00,
        "payoutFrequency": "monthly",
        "payoutType": "account_funded",
        "eaAllowed": true,
        "overnightAllowed": true,
        "weekendAllowed": true,
        "newsTrading": true,
        "consistencyRule": false
      },
      "dataVersion": "2024-Q1-v2",
      "lastVerified": "2024-01-10"
    }
  ],
  "totalFirmsReturned": 7,
  "filtersApplied": ["requireOvernightHolds=true"]
}

get_firm_rules

Complete rule set for a single firm, including edge cases and gotchas.

Parameters:

Parameter	Type	Required	Description
firm	string	Yes	Firm name: TopstepX, Apex, FTMO, MyFundedFutures, E8Markets, TradingPit, FundedTradingPlus
accountSize	number	No	Specific account size tier
includeGotchas	boolean	No	Include documented rule edge cases and traps (default: true)
includeHistory	boolean	No	Include rule change history (default: false)

The gotchas array is the highest-value output of this tool. Examples already documented:

• FTMO: Consistency rule means you can't make more than 30% of profits on any single day (can void your payout)
• Apex: Trailing drawdown is calculated from peak equity, not starting balance — this makes the effective drawdown tighter than advertised
• TopstepX: Express account profit splits change after month 6
• MyFundedFutures: EOD position flattening required (all positions must close before market close)

get_promotions

Current active promotions and discount codes.

Parameters:

Parameter	Type	Required	Description
firm	string	No	Specific firm (default: all firms)
includeExpired	boolean	No	Include recently expired promotions (default: false)

Note: Promotional data is manually verified and timestamped. Promotions change frequently — always verify directly with the firm before purchasing.

calculate_ev

This is the core tool. Calculate expected value for each firm's challenge given your trading statistics.

Parameters:

Parameter	Type	Required	Description
winRate	number	Yes	Historical win rate (0.0–1.0)
rrRatio	number	Yes	Average risk:reward ratio
avgTradesPerDay	number	Yes	Average number of trades per trading day
riskPerTradePercent	number	No	Risk per trade as % of account (default: 1.0)
consistencyPct	number	No	Day-to-day consistency score (0-1, 1=perfectly consistent)
accountSize	number	No	Preferred account size (default: 100000)
firmFilter	array	No	Limit to specific firms
requireOvernightHolds	boolean	No	Filter firms requiring EOD flat
requireEAAllowed	boolean	No	Filter to EA-compatible firms
simulationRuns	integer	No	Monte Carlo iterations (default: 10000, max: 100000)
sortBy	string	No	netEV, evPerDollarRisked, passProbability, breakEvenWinRate

Response:

{
  "evAnalysis": [
    {
      "firm": "Apex Trader Funding",
      "accountSize": 100000,
      "challengeCost": 207,
      "passProbability": 0.673,
      "expectedTimeToPass": "23 trading days",
      "payoutYear1": {
        "expectedMonthlyPayout": 1847,
        "expectedAnnualPayout": 22164
      },
      "ev": {
        "netEV": 14628,
        "evPerDollarInvested": 70.67,
        "breakEvenWinRate": 0.44,
        "breakEvenRR": 1.1
      },
      "riskMetrics": {
        "drawdownBreachProbability": 0.189,
        "expectedAttempts": 1.49,
        "totalExpectedCost": 308
      },
      "verdict": "POSITIVE_EV",
      "verdictDetail": "Your 52% win rate and 1.8 R:R creates a substantial edge over the 6% profit target with trailing drawdown. Expected to pass in 1.49 attempts. Main risk: trailing drawdown mechanics require discipline after early winning days."
    }
  ],
  "inputStats": {
    "impliedEdge": 0.136,
    "dailyExpectancy": 0.068,
    "kellyFraction": 0.213
  },
  "bestFirm": "Apex Trader Funding",
  "simulationRuns": 10000,
  "dataVersion": "2024-Q1-v3"
}

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Use Case Recipes

Recipe 1: "Which challenge should I take?"

Prompt:

"My backtest over 2 years: 48% win rate, 2.1 R:R average, 3 trades per day on NQ futures. I risk 0.8% per trade. I need overnight holds to be allowed, no consistency rule. Which prop firm has the highest EV for my strategy? Show me the top 3 with full math."

Recipe 2: "Is this challenge beatable at all?"

Prompt:

"I trade FTMO's $100K standard challenge (10% target, 5% daily DD, 10% total DD). My stats are 45% win rate and 1.5 R:R, 5 trades per day. What's my pass probability? What's the minimum win rate I'd need to break even on this challenge? Is it worth attempting?"

Recipe 3: Newsletter Comparison Table

Prompt:

"Create a comprehensive comparison table of all 7 prop firms for futures traders wanting a $100K account. Include: price, profit target, max drawdown type (trailing vs static), payout split, whether overnight holds are allowed, and whether EAs are allowed. Format as a markdown table suitable for a newsletter."

Recipe 4: Trading Coach Client Recommendation

Prompt:

"My student has a 55% win rate with 1.3 R:R. He averages 2 trades per day, always closes positions by end of day (no overnights), and does not use an EA. His budget is $200 max for the challenge fee. What firm should he try, and what does his EV look like?"

Recipe 5: "Check for current deals"

Prompt:

"Show me all current prop firm promotions and discount codes. I'm about to buy an Apex or FTMO challenge — is either running a discount right now?"

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Important Disclosures

This actor contains a static database, not live data. Prop firm rules change frequently — sometimes without public announcement. Always verify current rules directly with the firm before paying any challenge fee.

The EV calculator is a mathematical model, not a guarantee. Backtested win rates and R:R ratios often do not persist in live trading conditions. The model also does not account for: psychological factors, rule violations, platform issues, firm insolvency risk, or payout disputes.

Prop firm risk: Multiple prop trading firms have abruptly ceased operations or changed payout rules in 2022–2024. The data includes a firmRisk field with a qualitative assessment of each firm's apparent stability, but this is not financial advice.

Data version: Every response includes a dataVersion timestamp. Always check this — if the version is more than 60 days old, verify key rules directly with the firm.

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Claude Desktop Configuration

{
  "mcpServers": {
    "prop-firm-intel": {
      "command": "npx",
      "args": [
        "-y",
        "@apify/mcp-client",
        "--actor-id",
        "your-username/prop-firm-intel-mcp",
        "--token",
        "apify_api_XXXXXXXXXXXXXXXXXXXX"
      ]
    }
  }
}

Test prompt: "Compare TopstepX and Apex Trader Funding for a futures trader at the $100K level. What are the key rule differences?"

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Input Schema (Full)

{
  "mode": {
    "type": "string",
    "enum": ["compare", "firm_rules", "promotions", "calculate_ev"],
    "description": "Operating mode",
    "default": "compare"
  },
  "firm": {
    "type": "string",
    "enum": ["TopstepX", "Apex", "FTMO", "MyFundedFutures", "E8Markets", "TradingPit", "FundedTradingPlus"]
  },
  "winRate": {
    "type": "number",
    "minimum": 0.01,
    "maximum": 0.99,
    "description": "Historical win rate as decimal (e.g., 0.52 for 52%)"
  },
  "rrRatio": {
    "type": "number",
    "minimum": 0.1,
    "maximum": 20,
    "description": "Average risk to reward ratio (e.g., 1.8 means risk 1 to make 1.8)"
  },
  "avgTradesPerDay": {
    "type": "number",
    "minimum": 0.1,
    "maximum": 500,
    "description": "Average number of completed trades per trading day"
  },
  "accountSize": {
    "type": "number",
    "enum": [10000, 25000, 50000, 100000, 150000, 200000, 300000],
    "description": "Target account size in USD"
  },
  "requireOvernightHolds": { "type": "boolean", "default": false },
  "requireWeekendHolds": { "type": "boolean", "default": false },
  "requireEAAllowed": { "type": "boolean", "default": false },
  "requireNewsTrading": { "type": "boolean", "default": false },
  "simulationRuns": {
    "type": "integer",
    "minimum": 1000,
    "maximum": 100000,
    "default": 10000
  },
  "sortBy": {
    "type": "string",
    "enum": ["netEV", "evPerDollarRisked", "passProbability", "breakEvenWinRate", "price"],
    "default": "netEV"
  }
}

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Pricing & Usage

Tier	Price	Includes
Free	$0	50 queries/month (compare + firm_rules only)
Trader	$9/month	500 queries/month + EV calculator
Coach	$29/month	5,000 queries/month + batch + promotions monitor

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Data Source & Verification

• Source: Manually compiled from official firm websites, terms of service, and verified trader reports
• Verification cadence: Monthly audit against firm websites; emergency updates when major rule changes are reported by community
• Data version format: YYYY-QN-vN (e.g., 2024-Q1-v3 = third update in Q1 2024)
• Community contribution: Rule change reports accepted via GitHub Issues; verified changes credited

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Technical Notes

• EV calculator uses Monte Carlo simulation (default 10,000 runs); set simulationRuns: 100000 for higher precision at the cost of ~3s additional processing time
• The Kelly Fraction is calculated and returned for reference; it should not be used directly as the risk-per-trade input for live trading without a significant fraction (suggest 1/4 Kelly at most)
• Drawdown simulation uses geometric Brownian motion with drift; does not model fat-tail events or correlated loss streaks — real performance will have higher drawdown tail risk than modeled
• Trailing drawdown mechanics are simulated correctly: drawdown tracks from peak equity, not starting balance

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Support & Issues

• GitHub: github.com/your-username/prop-firm-intel-mcp
• Rule change reports: Submit via GitHub Issues with source documentation
• Email: support@your-domain.com

This actor is not affiliated with any prop trading firm. Not financial advice. Prop trading involves substantial risk of loss.