varrd 0.3.0

Trading edge discovery. Test any idea with real market data.

VARRD

Turn any trading idea into a statistically validated edge — or find out it doesn't work for $0.25.

pip install varrd

Ask it anything

varrd research "Does buying SPY after a 3-day losing streak actually work?"

varrd research "When VIX spikes above 30, is there a bounce in ES?"

varrd research "Is there a seasonal pattern in wheat before harvest?"

varrd research "What happens to gold when the dollar drops 3 days straight?"

varrd research "Does Bitcoin rally after the halving?"

varrd research "When crude oil drops 5% in a week, what happens next?"

Every question gets real data, a chart with signals marked, a statistical test, and a definitive answer.

What you get back

Edge found

STRONG EDGE — Statistically significant vs both zero and market baseline.

  Direction:    LONG
  Win Rate:     62%
  Sharpe:       1.45
  Signals:      247

  Trade Setup:
    Entry:       $5,150.25
    Stop Loss:   $5,122.00
    Take Profit: $5,192.50
    Risk/Reward: 1:1.5

No edge

NO EDGE — Neither test passed. No tradeable signal found.

You found out for 25 cents instead of $25,000 in live losses.

Both are valuable results.

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How it works

Your idea (plain English)
     ↓
  Load real market data — stocks, futures, crypto
     ↓
  Chart the pattern — see actual signals on price history
     ↓
  You approve — sanity check before spending statistical power
     ↓
  Statistical test — event study with proper controls
     ↓
  Verdict:  STRONG EDGE / MARGINAL / NO EDGE
     ↓
  Trade setup — exact entry, stop-loss, take-profit in dollars

A typical session is 3–5 turns and costs ~$0.25.

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Quick start — Python

from varrd import VARRD

v = VARRD()  # auto-creates free account, $2 in credits

# Research a trading idea
r = v.research("When RSI drops below 25 on ES, is there a bounce?")
r = v.research("test it", session_id=r.session_id)

print(r.context.edge_verdict)  # "STRONG EDGE" / "NO EDGE"

# Get exact trade levels
r = v.research("show me the trade setup", session_id=r.session_id)

# What's firing right now across all your strategies?
signals = v.scan(only_firing=True)
for s in signals.results:
    print(f"{s.name}: {s.direction} {s.market} @ ${s.entry_price}")

# Let VARRD discover edges autonomously
result = v.discover("mean reversion on futures")
print(result.edge_verdict, result.market, result.win_rate)

Quick start — CLI

# Full research workflow (auto-follows chart → test → trade setup)
varrd research "When wheat drops 3 days in a row, is there a snap-back?"

# What's firing right now?
varrd scan --only-firing

# Search saved strategies
varrd search "momentum on grains"

# Let VARRD discover edges on its own
varrd discover "mean reversion on futures"

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Use with AI agents

Claude Desktop / Claude Code / Cursor

Add to your MCP config — no API key needed:

{
  "mcpServers": {
    "varrd": {
      "transport": {
        "type": "streamable-http",
        "url": "https://app.varrd.com/mcp"
      }
    }
  }
}

Then just ask: "Is there a pattern when gold spikes after a Fed rate decision?"

CrewAI

from crewai import Agent, Task, Crew

researcher = Agent(
    role="Trading Researcher",
    goal="Find statistically validated trading edges",
    backstory="You are a quantitative researcher who tests trading ideas rigorously.",
    mcps=[{"type": "streamable-http", "url": "https://app.varrd.com/mcp"}]
)

task = Task(
    description="Research whether RSI oversold conditions on ES lead to a bounce within 5 days.",
    agent=researcher,
    expected_output="Edge verdict with trade setup if edge is found."
)

crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()

LangChain / LangGraph

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_anthropic import ChatAnthropic

model = ChatAnthropic(model="claude-sonnet-4-20250514")

async with MultiServerMCPClient({
    "varrd": {"url": "https://app.varrd.com/mcp", "transport": "streamable_http"}
}) as client:
    agent = create_react_agent(model, client.get_tools())
    result = await agent.ainvoke({"messages": [
        {"role": "user", "content": "Does gold rally when the dollar drops 3 days in a row?"}
    ]})

Raw MCP (any client)

# Any MCP-compatible client can connect to:
https://app.varrd.com/mcp
# Transport: Streamable HTTP | No auth required | $2 free credits

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8 statistical guardrails (infrastructure-enforced)

Every test runs through these automatically. You can't skip them.

Guardrail	What It Prevents
K-Tracking	Tests 50 variations of the same idea? Significance bar goes up automatically.
Bonferroni Correction	Multiple comparison penalty. No p-hacking.
OOS Lock	Out-of-sample is one shot. Can't re-run after seeing results.
Lookahead Detection	Catches formulas that accidentally use future data.
Tools Calculate, AI Interprets	Every number comes from real data. AI never fabricates stats.
Chart → Approve → Test	You see and approve the pattern before spending statistical power.
Fingerprint Dedup	Can't retest the same formula/market/horizon twice.
No Post-OOS Optimization	Parameters lock after out-of-sample validates.

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Data coverage

Asset Class	Markets	Timeframes
Futures (CME)	ES, NQ, CL, GC, SI, ZW, ZC, ZS, ZB, TY, HG, NG + 20 more	1h and above
Stocks / ETFs	Any US equity	Daily
Crypto (Binance)	BTC, ETH, SOL + more	10min and above

15,000+ instruments total.

MCP tools

Tool	Cost	What It Does
research	~$0.25	Multi-turn quant research. Orchestrates 15 internal tools.
autonomous_research	~$0.25	AI discovers edges for you. Give it a topic, get validated results.
scan	Free	Scan strategies against live data. Fresh entry/stop/target prices.
search	Free	Find strategies by keyword or natural language.
get_hypothesis	Free	Full details on any strategy.
check_balance	Free	View credits and available packs.
buy_credits	Free	Buy credits with USDC on Base or Stripe.
reset_session	Free	Kill a broken session and start fresh.

Pricing

• $2 free on signup — enough for 6–8 research sessions
• Research: ~$0.20–0.30 per idea tested
• Discovery (autonomous): ~$0.20–0.30
• ELROND council (8 expert investigators): ~$0.40–0.60
• Multi-market (3+ markets): ~$1
• Scan, search, balance: Always free
• Credit packs: $5 / $20 / $50 via Stripe
• Credits never expire

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Examples

See examples/ for runnable scripts:

• quick_start.py — 5 lines to scan all strategies
• research_idea.py — Full multi-turn research workflow
• multi_idea_loop.py — Test many ideas in a loop
• scan_portfolio.py — Portfolio scan with trade levels
• mcp_config.json — MCP config for Claude Desktop / Cursor

For AI agent builders

See AGENTS.md for the complete integration guide — tool reference, response formats, authentication, and workflow patterns.

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Links

• Web app: app.varrd.com
• Website: varrd.com
• MCP endpoint: https://app.varrd.com/mcp
• PyPI: pypi.org/project/varrd