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VARRD — Statistically Validated Trading Edges + AI Research Engine MCP server

online · 100% uptime
by augiemazza·io.github.augiemazza/varrd·v1.0.5·24 stars

Validated trading edges across futures, equities, crypto. Live signals, full audit trail.

B83/100grade B
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VARRD — Statistically Validated Trading Edges + AI Research Engine tools (9, 2 write)

write = sends, deletes, buys or posts
  • autonomous_varrd_aiFree

    Point VARRD's autonomous AI in a direction and let it discover edges for you. Give it a topic and it draws from one of the most comprehensive market structure knowledge graphs ever built — containing ideologies and theories, not statistics — so it generates genuinely novel hypotheses rather than overfitting to what already worked. BEST FOR: Exploring a space broadly. Give it 'momentum on grains' and it might test wheat seasonal patterns, corn spread reversals, or soybean crush ratio momentum. It propagates from your seed idea into related concepts you might not think of. Returns a complete result — edge or no edge, stats, trade setup. Each call tests ONE hypothesis through the full pipeline (~$0.25/idea). Call again for another idea. Use 'varrd_ai' instead when YOU have a specific idea to test and want full control over each step.

  • buy_creditswrite actionFree

    Buy credits for the edge library and AI research. Default $5 minimum. Free — no credits consumed to call this. TWO PAYMENT METHODS: card (default): Returns a Stripe Checkout link for your user to click and pay. After payment, call check_balance to confirm credits were added. crypto: USDC on Base. Fully autonomous — no human needed. Three steps: 1. buy_credits(payment_method='crypto') → returns deposit address + payment_intent_id 2. Send USDC to the deposit address (use your wallet tool) 3. buy_credits(payment_intent_id='pi_...') → confirms payment, credits added instantly If you have wallet access, this is the fastest path — fully machine-to-machine.

  • check_balanceFree

    Check your credit balance and see available credit packs. Free — no credits consumed. Also auto-detects completed payments — call this after your user pays via a checkout link to confirm credits were added. If payment went through, the response includes recovered_cents.

  • get_briefedFree

    Get a personalized market news briefing based on your validated edge library. Profiles your strategies, searches today's news for the instruments and setups you actually trade, and writes a concise digest connecting each headline to your specific book. Each news item includes a ↳ line tying it to your actual positions and edges (e.g. 'your ES momentum setups', 'your GC mean-reversion edge'). Requires at least 5 strong edges in your library. Costs credits.

  • get_hypothesisFree

    Get full detail for a specific hypothesis/strategy. Returns formula, entry/exit rules, direction, performance metrics (win rate, Sharpe, profit factor, max drawdown), version history, and trade levels. Everything an agent needs to understand and act on a strategy.

  • reset_sessionwrite actionFree

    Kill a broken research session and start fresh. Use this when a session gets stuck, produces errors, or enters a bad state. Free — no credits consumed. After resetting, call research without a session_id to start a new clean session.

  • searchFree

    Search your saved hypotheses by keyword or natural language query. Returns matching strategies ranked by relevance, with key stats (win rate, Sharpe, edge status). Use this to find strategies you've already validated.

  • varrd_aiFree

    Talk to VARRD AI (~$0.25/turn). Describe any trading idea in plain language and the system handles everything — loading decades of market data, charting your pattern, running statistical tests, backtesting with stops, and generating exact trade setups. MULTI-TURN: First call creates a session. Keep calling with the same session_id, following context.next_actions each time. 1. Your idea -> VARRD charts pattern 2. 'test it' -> statistical test (event study or backtest) 3. 'show me the trade setup' -> exact entry/stop/target prices HYPOTHESIS INTEGRITY (critical): VARRD tests ONE hypothesis at a time — one formula, one setup. Never combine multiple setups into one formula or ask to 'test all' — each idea must be tested as a separate hypothesis for the statistics to be valid. Say 'start a new hypothesis' between ideas to reset cleanly. - ALLOWED: Test the SAME setup across multiple markets ('test this on ES, NQ, and CL') — same formula, different data. - NOT ALLOWED: Test multiple DIFFERENT formulas/setups at once — each is a separate hypothesis requiring its own chart-test-result cycle. If ELROND council returns 4 setups, test each one separately: chart setup 1 -> test -> results -> 'start new hypothesis' -> chart setup 2 -> etc. KEY CAPABILITIES you can ask for: - 'Use the ELROND council on [market]' -> 8 expert investigators - 'Optimize the stop loss and take profit' -> SL/TP grid search - 'Test this on ES, NQ, and CL' -> multi-market testing - 'Simulate trading this with 1.5 ATR stop' -> backtest with stops EDGE VERDICTS in context.edge_verdict after testing: - STRONG EDGE: Significant vs zero AND vs market baseline - MARGINAL: Significant vs zero only (beats nothing, but real signal) - PINNED: Significant vs market only (flat returns but different from market) - NO EDGE: Neither significant test passed TERMINAL STATES: Stop when context.has_edge is true (edge found) or false (no edge — valid result). Always read context.next_actions.

  • varrd_edgesFree

    THE PRIMARY TOOL — start here. FREE at depth=0, always safe to call. Live feed of THIS USER'S OWN statistically validated trading edges — the ones on their account — running 24/7 against real market data. See which of YOUR edges are firing right now, get trade levels, or audit the full methodology. Scoped to the connected account: if the user has no edges yet, this returns none (it is NOT a general/shared library). THREE TIERS: depth=0 (FREE — call this first): See which of YOUR edges are firing right now, pending bar close, or actively in trades. Markets and status only — no direction, no stats. Get a sense of what's live. depth=1 ($0.50): Unlock direction, occurrence count, EV/trade, stop-loss, take-profit, hold horizon, and current entry prices for ALL active edges in one request. depth=2 ($1 per edge, $5 for all): Full methodology — the actual formula, setup code, how the edge was discovered, edge decay analysis, complete performance analytics (Sharpe, drawdown, equity curve, profit factor). Machine-readable so any AI can audit the statistical rigor. Includes drill-down sections (free after purchase): setup_code, horizons, analytics, occurrences, and view (interactive chart link for your user, 15 min). Every edge in this library is Bonferroni-corrected, tested against both zero returns and market baseline, with K-tracking to prevent p-hacking. Out-of-sample validated. Full transparency.

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

1 high
  • –Code scanremote-only server, no package to scann/a
  • Live reliabilityremote reachable in 401ms20/20
  • Tool poisoning9 tool descriptions checked15/15
  • Auth qualityopen endpoint exposes 2 write-action tools with no auth3/15
  • Maintenancelast push 27 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year9/10

Findings (1)

  • highWrite-action tools reachable without authenticationauth.open-write
Overall 83/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

Install VARRD — Statistically Validated Trading Edges + AI Research Engine in Claude Code, Cursor or VS Code

claude mcp add --transport http varrd https://app.varrd.com/mcp
Add to Cursor

What the publisher says

From the VARRD — Statistically Validated Trading Edges + AI Research Engine repository's README, as published. We do not edit it. Read it on GitHub

VARRD

<!-- mcp-name: io.github.varrdinc/varrd -->

The governed live edge layer. Statistically validated market behaviors, monitored in real time.

Web App · MCP Endpoint · PyPI · varrd.com

Every edge shows exact entry, stop, target, and the full statistical methodology behind it.

Equity curves, Monte Carlo simulations, regime analysis, edge decay, and full audit trail.

Two ways to use VARRD

1. Tell your AI. Add the MCP config below, then ask: "What VARRD edges are firing right now?" or "What happens to gold when silver ETFs are making 100-day new lows?" Your AI browses the edge library, shows you what's actionable, and can test any idea you throw at it.

2. Use the web app. Go to app.varrd.com, sign up, and do the same thing — browse the edge library, ask questions like "Is there a seasonal pattern in wheat before harvest?", and watch the full research pipeline run visually.

{
  "mcpServers": {
    "varrd": { "url": "https://app.varrd.com/mcp" }
  }
}

Works with Claude Desktop, Cursor, OpenBB, or any MCP client. No API key needed.

What VARRD does

VARRD turns trading ideas into quantitative formulas using a domain-specific language we built from the ground up — purpose-built to express market behaviors in a way that's both machine-testable and human-readable. Those formulas are then tested with the right guardrails so the results actually mean something.

The AI generates hypotheses. A purpose-built backtesting engine does the math. The AI never calculates statistics, never fabricates results, and never touches the numbers. Every stat comes from a deterministic computation running in a sandboxed kernel. This matters because most people's first question is: "How do I know the AI isn't just making this up?" It can't. The engine is separate from the model.

VARRD also maintains a growing library of validated edges — patterns that survived the full testing gauntlet — running 24/7 against live market data across futures, equities, and crypto. When an edge fires, you get exact entry, stop, target, hold period, and the complete audit trail of how it was discovered, tested, and validated.

Full transparency

Every edge in the library shows you everything. Not summaries — the actual work.

How it was found: The discovery story — what pattern was hypothesized, why it might work, what market structure theory it's based on. You can read the exact thinking that led to the formula.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

VARRD — Statistically Validated Trading Edges + AI Research Engine: common questions

Is VARRD — Statistically Validated Trading Edges + AI Research Engine MCP server safe?
Mostly: it is graded B (83/100). Read the VARRD — Statistically Validated Trading Edges + AI Research Engine safety report
How do I install VARRD — Statistically Validated Trading Edges + AI Research Engine?
It runs remotely at app.varrd.com. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
Does VARRD — Statistically Validated Trading Edges + AI Research Engine need an API key?
Not as far as the registry entry and our scan can tell: no credentials are declared or required.
Is VARRD — Statistically Validated Trading Edges + AI Research Engine maintained?
The last commit was 28 days ago (2026-08-31). The latest release is v1.0.5.
Is VARRD — Statistically Validated Trading Edges + AI Research Engine up?
100% of our last 28 checks got an answer. We check remote servers about four times a day.
What can I use instead of VARRD — Statistically Validated Trading Edges + AI Research Engine?
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