# VARRD — Statistically Validated Trading Edges + AI Research Engine (remote · app.varrd.com)

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

- Trust score: 65/100 (medium)
- Change this week: +2
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `app.varrd.com`: 65/100 (this document), [markdown](https://verifymcp.io/servers/augiemazza-varrd/app.md), [page](https://verifymcp.io/servers/augiemazza-varrd/app)

## Channel facts

- Endpoint: `https://app.varrd.com/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.5`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation check failed: no authorisation is required to call this server, and it exposes a tool marked destructive (reset_session).
  - HTTPS is enforced; there's no plaintext access path.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 66/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 5846 tokens (~531/item across 11 items; 9 tools + 2 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (89% of tools); any adoption earns full credit.
- **Capabilities**: 60/100
  - Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http augiemazza-varrd https://app.varrd.com/mcp
```

### Codex

```toml
[mcp_servers.augiemazza-varrd]
url = "https://app.varrd.com/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "augiemazza-varrd": {
      "type": "remote",
      "url": "https://app.varrd.com/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add augiemazza-varrd --url https://app.varrd.com/mcp --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  augiemazza-varrd:
    url: "https://app.varrd.com/mcp"
```

### Other

```json
{
  "mcpServers": {
    "augiemazza-varrd": {
      "type": "http",
      "url": "https://app.varrd.com/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 65, +1)

No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 64, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 63, −1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-28 (score 64, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 63, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 62)

First indexed and scored.

## MCP tools (9)

### `varrd_edges` (~534 tokens)

THE PRIMARY TOOL — start here. FREE at depth=0, always safe to call.

Live feed of statistically validated trading edges running 24/7 against real market data. See what's firing right now, get trade levels, or audit the full methodology.

THREE TIERS:
  depth=0 (FREE — call this first): See which markets have edges 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.

Input parameters:

- `asset_class` (string): Filter by asset class: 'futures', 'equities', 'crypto'.
- `depth` (integer): 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.
- `direction` (string): Filter by direction: 'LONG' or 'SHORT'.
- `edge_id` (string): Specific edge ID for depth 1 or 2 detail. Omit to see all edges.
- `market` (string): Filter by market symbol (e.g. 'ES', 'GC'). Omit to see all.
- `section` (string): 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.
- `status` (string): Filter by status: 'firing', 'pending', 'active', or omit for all.
- `timeframe` (string): Filter by timeframe: '60min', '120min', '240min', '480min', 'daily', 'weekly'.

### `varrd_ai` (~547 tokens)

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.

Input parameters:

- `message` (string, required): Your trading idea, research question, or instruction (e.g. 'test it', 'show trade setup').
- `session_id` (string): Session ID from a previous call. Omit to start a new research session.

Output parameters:

- `context` (object): Workflow state, edge verdict, next actions
- `session_id` (string): Session ID for multi-turn conversation
- `text` (string): AI response text
- `widgets` (array): Chart, event study, backtest, or trade setup widgets

### `search` (~96 tokens)

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.

Input parameters:

- `limit` (integer): Max results to return.
- `market` (string): Optional market filter.
- `query` (string, required): Search query — keywords or natural language (e.g. 'momentum strategies', 'RSI oversold').

Output parameters:

- `method` (string): Search method: embedding or keyword
- `query` (string)
- `results` (array): Matching strategies with win rate, Sharpe, similarity

### `get_hypothesis` (~82 tokens)

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.

Input parameters:

- `hypothesis_id` (string, required): The hypothesis ID (from search or scan results).

Output parameters:

- `direction` (string)
- `formula` (string)
- `horizon_results` (array)
- `hypothesis_id` (string)
- `name` (string)
- `win_rate` (number)

### `check_balance` (~60 tokens)

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.

Output parameters:

- `balance_cents` (integer): Current credit balance in cents
- `credit_packs` (array): Available credit packs for purchase
- `recovered_cents` (integer): Credits recovered from completed payments (if any)

### `buy_credits` (~253 tokens)

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.

Input parameters:

- `amount_cents` (integer): Amount in cents (default 500 = $5.00). Minimum $5.
- `payment_intent_id` (string): For crypto: Stripe PaymentIntent ID from a previous buy_credits call. Pass after sending USDC to confirm.
- `payment_method` (string): Payment method: 'card' (default, Stripe Checkout) or 'crypto' (USDC on Base).

Output parameters:

- `checkout_url` (string): Stripe Checkout link for card payment
- `current_balance_cents` (integer)
- `deposit` (object): USDC deposit address for crypto payment

### `reset_session` (~69 tokens)

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.

Input parameters:

- `session_id` (string, required): The session_id to reset.

Output parameters:

- `message` (string)
- `reset` (boolean)

### `autonomous_varrd_ai` (~332 tokens)

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.

Input parameters:

- `asset_classes` (array): Limit to specific asset classes. Default: all.
- `context` (array): Prior conversation context — recent user queries to use as research inspiration. Optional.
- `markets` (array): Focus on specific markets (e.g. ['ES', 'NQ']). Omit for VARRD to choose.
- `search_mode` (string): focused = stay close to topic. explore = creative freedom. Default: focused.
- `test_type` (string): Type of statistical test. Default: event_study.
- `topic` (string, required): Research topic or trading idea (e.g. 'BTC 240min short setups', 'momentum on grains', 'mean reversion after VIX spikes').

Output parameters:

- `context` (object): has_edge, edge_verdict, workflow_state
- `session_id` (string)
- `text` (string): Full research result with edge verdict
- `widgets` (array): Chart, test results, trade setup

### `get_briefed` (~101 tokens)

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.

Output parameters:

- `news` (string): Personalized market news digest
- `profile` (string): Trader profile based on edge library
- `strong_count` (integer): Number of strong edges in library

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/augiemazza-varrd/app#diagnostics

## Score history

- 2026-08-03: 65
- 2026-08-02: 65
- 2026-08-01: 64
- 2026-07-31: 64
- 2026-07-30: 63
- 2026-07-29: 64
- 2026-07-28: 64
- 2026-07-27: 63
- 2026-07-26: 62

## Links

- Remote endpoint: https://app.varrd.com/mcp
- Repository: https://github.com/augiemazza/varrd
- Website: https://www.varrd.com/
- Changelog RSS feed: https://verifymcp.io/servers/augiemazza-varrd/app/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/augiemazza-varrd/app/changelog.json
- HTML version of this page: https://verifymcp.io/servers/augiemazza-varrd/app