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VARRD — Statistically Validated Trading Edges + AI Research Engine

io.github.augiemazza/varrd
Finance & Investing Public & reachable MCP 2026-07-28

What this MCP does

Researches, backtests, validates, and monitors trading hypotheses and statistically tested edges across futures, equities, and crypto markets.

Capabilities

Tools

9 tools
autonomous_varrd_ai
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.
Open world
Input schema 
{'type': 'object', 'required': ['topic'], 'properties': {'topic': {'type': 'string', 'description': "Research topic or trading idea (e.g. 'BTC 240min short setups', 'momentum on grains', 'mean reversion after VIX spikes')."}, 'context': {'type': 'array', 'items': {'type': 'string'}, 'description': 'Prior conversation context — recent user queries to use as research inspiration. Optional.'}, 'markets': {'type': 'array', 'items': {'type': 'string'}, 'description': "Focus on specific markets (e.g. ['ES', 'NQ']). Omit for VARRD to choose."}, 'test_type': {'enum': ['event_study', 'backtest', 'both'], 'type': 'string', 'default': 'event_study', 'description': 'Type of statistical test. Default: event_study.'}, 'search_mode': {'enum': ['focused', 'explore'], 'type': 'string', 'default': 'focused', 'description': 'focused = stay close to topic. explore = creative freedom. Default: focused.'}, 'asset_classes': {'type': 'array', 'items': {'enum': ['crypto', 'futures', 'equities'], 'type': 'string'}, 'description': 'Limit to specific asset classes. Default: all.'}}}
Output schema 
{'type': 'object', 'properties': {'text': {'type': 'string', 'description': 'Full research result with edge verdict'}, 'context': {'type': 'object', 'description': 'has_edge, edge_verdict, workflow_state'}, 'widgets': {'type': 'array', 'description': 'Chart, test results, trade setup'}, 'session_id': {'type': 'string'}}}
buy_credits
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.
Open world
Input schema 
{'type': 'object', 'properties': {'amount_cents': {'type': 'integer', 'default': 500, 'description': 'Amount in cents (default 500 = $5.00). Minimum $5.'}, 'payment_method': {'type': 'string', 'default': 'card', 'description': "Payment method: 'card' (default, Stripe Checkout) or 'crypto' (USDC on Base)."}, 'payment_intent_id': {'type': 'string', 'description': 'For crypto: Stripe PaymentIntent ID from a previous buy_credits call. Pass after sending USDC to confirm.'}}}
Output schema 
{'type': 'object', 'properties': {'deposit': {'type': 'object', 'description': 'USDC deposit address for crypto payment'}, 'checkout_url': {'type': 'string', 'description': 'Stripe Checkout link for card payment'}, 'current_balance_cents': {'type': 'integer'}}}
check_balance
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.
Read only Idempotent
Input schema 
{'type': 'object', 'properties': {}}
Output schema 
{'type': 'object', 'properties': {'credit_packs': {'type': 'array', 'description': 'Available credit packs for purchase'}, 'balance_cents': {'type': 'integer', 'description': 'Current credit balance in cents'}, 'recovered_cents': {'type': 'integer', 'description': 'Credits recovered from completed payments (if any)'}}}
get_briefed
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.
Read only Open world
Input schema 
{'type': 'object', 'properties': {}}
Output schema 
{'type': 'object', 'properties': {'news': {'type': 'string', 'description': 'Personalized market news digest'}, 'profile': {'type': 'string', 'description': 'Trader profile based on edge library'}, 'strong_count': {'type': 'integer', 'description': 'Number of strong edges in library'}}}
get_hypothesis
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.
Read only Idempotent
Input schema 
{'type': 'object', 'required': ['hypothesis_id'], 'properties': {'hypothesis_id': {'type': 'string', 'description': 'The hypothesis ID — from varrd_edges (any depth), search, or scan results.'}}}
Output schema 
{'type': 'object', 'properties': {'name': {'type': 'string'}, 'formula': {'type': 'string'}, 'win_rate': {'type': 'number'}, 'direction': {'type': 'string'}, 'hypothesis_id': {'type': 'string'}, 'horizon_results': {'type': 'array'}}}
reset_session
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.
Destructive Idempotent
Input schema 
{'type': 'object', 'required': ['session_id'], 'properties': {'session_id': {'type': 'string', 'description': 'The session_id to reset.'}}}
Output schema 
{'type': 'object', 'properties': {'reset': {'type': 'boolean'}, 'message': {'type': 'string'}}}
search
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.
Read only Idempotent
Input schema 
{'type': 'object', 'required': ['query'], 'properties': {'limit': {'type': 'integer', 'default': 10, 'description': 'Max results to return.'}, 'query': {'type': 'string', 'description': "Search query — keywords or natural language (e.g. 'momentum strategies', 'RSI oversold')."}, 'market': {'type': 'string', 'description': 'Optional market filter.'}}}
Output schema 
{'type': 'object', 'properties': {'query': {'type': 'string'}, 'method': {'type': 'string', 'description': 'Search method: embedding or keyword'}, 'results': {'type': 'array', 'description': 'Matching strategies with win rate, Sharpe, similarity'}}}
varrd_ai
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.
Open world
Input schema 
{'type': 'object', 'required': ['message'], 'properties': {'message': {'type': 'string', 'description': "Your trading idea, research question, or instruction (e.g. 'test it', 'show trade setup')."}, 'session_id': {'type': 'string', 'description': 'Session ID from a previous call. Omit to start a new research session.'}}}
Output schema 
{'type': 'object', 'properties': {'text': {'type': 'string', 'description': 'AI response text'}, 'context': {'type': 'object', 'description': 'Workflow state, edge verdict, next actions'}, 'widgets': {'type': 'array', 'description': 'Chart, event study, backtest, or trade setup widgets'}, 'session_id': {'type': 'string', 'description': 'Session ID for multi-turn conversation'}}}
varrd_edges
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.
Read only Idempotent
Input schema 
{'type': 'object', 'properties': {'depth': {'enum': [0, 1, 2], 'type': 'integer', 'default': 0, 'description': '0=free (markets + status), 1=$0.50 (direction, stats, trade levels for ALL active edges), 2=$1/edge or $5/all (full methodology + performance). Cheaper than a coffee.'}, 'market': {'type': 'string', 'description': "Filter by market symbol (e.g. 'ES', 'GC'). Omit to see all."}, 'status': {'type': 'string', 'description': "Filter by status: 'firing', 'pending', 'active', or omit for all."}, 'edge_id': {'type': 'string', 'description': 'Specific edge ID for depth 1 or 2 detail. Omit to see all edges.'}, 'section': {'type': 'string', 'description': 'Drill into a specific section of a depth=2 edge (free after purchase). Options: setup_code, horizons, analytics, occurrences, view. Omit to get the overview directory.'}, 'direction': {'enum': ['LONG', 'SHORT'], 'type': 'string', 'description': "Filter by direction: 'LONG' or 'SHORT'."}, 'timeframe': {'type': 'string', 'description': "Filter by timeframe: '60min', '120min', '240min', '480min', 'daily', 'weekly'."}, 'asset_class': {'enum': ['futures', 'equities', 'crypto'], 'type': 'string', 'description': "Filter by asset class: 'futures', 'equities', 'crypto'."}}}
History

Recent tool changes

Added
get_briefed
Sept. 17, 2026, 12:40 p.m.
Added
autonomous_varrd_ai
Sept. 17, 2026, 12:40 p.m.
Added
reset_session
Sept. 17, 2026, 12:40 p.m.
Added
buy_credits
Sept. 17, 2026, 12:40 p.m.
Added
check_balance
Sept. 17, 2026, 12:40 p.m.
Added
get_hypothesis
Sept. 17, 2026, 12:40 p.m.
Added
search
Sept. 17, 2026, 12:40 p.m.
Added
varrd_ai
Sept. 17, 2026, 12:40 p.m.
Added
varrd_edges
Sept. 17, 2026, 12:40 p.m.
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