@cryptyx/mcp-server

@cryptyx/mcp-server

🔔 Deprecation notice (2026-07)

This package is entering deprecation. The flagship CRYPTYX MCP integration is now the OAuth 2.1 Remote MCP surface at https://cryptyx.ai/api/mcp — no config file editing, no API key management, revocable per-app, enterprise/SOC 2 ready.

Migrate at cryptyx.ai/mcp. Paste one URL into Claude.ai, Cursor, or any MCP-compatible client and go.

This npm package remains supported through 2026-12-31 for clients that don't yet support OAuth MCP (older Cursor releases, some enterprise agent platforms). Your existing cx_* API key continues to work throughout — no forced migration timeline for existing users.

New users: use the OAuth path from day one. Existing users: migrate on your schedule. See migration guide (or just re-add via cryptyx.ai/mcp — takes 30 seconds).

CRYPTYX — the intelligence layer for digital assets.

Institutional-grade digital asset intelligence delivered via the Model Context Protocol and a human-facing CLI. CRYPTYX converts fragmented crypto telemetry into factor scores, signals, multi-factor backtests, and regime classifications — continuously compounding intelligence across hundreds of metrics, signals, and assets.

Not a data proxy. A quant research platform. 30 tools across 670+ metrics, 8 factor classes, 160 signals, 17 IC-weighted composites, ~200 tracked assets, and a daily-updating signal registry — now including institutional trigger evaluation (Sortino, MDD, profit factor, walk-forward IS/OOS) as of v0.8.0. Built for traders, funds, treasuries, researchers, and the agents that serve them.

Execution is complementary — and venue-neutral. Use CRYPTYX alongside any exchange execution rail. Reference handshakes shipped for Coinbase, OKX, Kraken, Binance, and Hyperliquid — each ~150 lines, one three-step pattern: pay CRYPTYX → apply institutional gate → execute on the venue. Fork any of them for your target venue.

Install

MCP Server (for AI agents)

npx @cryptyx/mcp-server

CLI (for humans and scripts)

npx cryptyx --help

Or install globally:

npm install -g @cryptyx/mcp-server
cryptyx snapshot

Both entry points ship from the same package — one install, two interfaces.

CLI Quick Start

# Save your API key (persists to ~/.config/cryptyx/config.json)
cryptyx config set-key cx_your_api_key

# Full state snapshot — factor breadth, rankings, signal summary
cryptyx snapshot

# Market data for all assets
cryptyx market

# Factor scores for a single asset
cryptyx factors BTC

# Today's signal firings
cryptyx signals

# Top 10 signals by information coefficient
cryptyx signals top

# Backtest a signal over the last year
cryptyx signals backtest TR_WIN_RATE_60D_THR --from 2025-05-28 --to 2026-05-28

# Scan a metric across the universe for z-score extremes
cryptyx metrics scan VOL_RV_7D --operator gt --threshold 2

# Raw JSON output (pipe to jq, scripts, cron)
cryptyx market --json | jq '.[] | select(.composite_rank <= 10)'

Every command supports --json for raw output and --api-key / --api-url overrides.

CLI Commands

Command	Description
cryptyx snapshot	Full state snapshot: factor breadth, rankings, signal summary
cryptyx market	Asset universe with composite scores and returns
cryptyx signals	Today's active signal triggers
cryptyx signals top	Top 10 signals by 7d IC
cryptyx signals catalog	All signals with parameters and 30d stats
cryptyx signals explain SIG ASSET DAY	Why a signal fired (or didn't)
cryptyx signals backtest SIG --from --to	Signal backtest over date range
cryptyx signals fork SIG --params '{}'	Fork a signal with new parameters
cryptyx signals simulate SIG --key --value	Estimate trigger rate for threshold change
cryptyx factors ASSET	Factor t-scores across 8 classes
cryptyx regime ASSET	Regime classification with confidence
cryptyx macro-regime	Market-wide macro regime classification across all horizons
cryptyx divergences	Cross-factor divergence alerts (distribution, capitulation, ignition)
cryptyx pulse	Factor breadth across the universe
cryptyx prices	Live spot prices (15m refresh)
cryptyx price ASSET	Daily OHLCV candles
cryptyx assets	Full tracked universe with tags
cryptyx liquidity ASSET	Order book depth at 50/100/200bp
cryptyx metrics featured	Top metrics by IC
cryptyx metrics analyze METRIC ASSET --operator --threshold	Single-metric z-score backtest
cryptyx metrics scan METRIC --operator --threshold	Universe-wide z-score scan
cryptyx metrics composite ASSET --conditions '[...]'	Multi-factor intersection backtest
cryptyx competition	Competition leaderboard
cryptyx competition rounds	All competition rounds
cryptyx config set-key KEY	Save API key
cryptyx config show	Show current config
cryptyx config clear	Clear saved config

MCP Configuration

Claude Desktop

{
  "mcpServers": {
    "cryptyx": {
      "command": "npx",
      "args": ["@cryptyx/mcp-server"],
      "env": {
        "CRYPTYX_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Code

claude mcp add cryptyx -- npx @cryptyx/mcp-server
export CRYPTYX_API_KEY=cx_your_key

Remote HTTP (Claude.ai Connectors)

Endpoint:  https://cryptyx.ai/api/mcp
Transport: Streamable HTTP (JSON-RPC 2.0 over POST)
Auth:      Bearer token (cx_* API key)

Environment Variables

Variable	Required	Default	Description
CRYPTYX_API_KEY	Yes	—	API key from cryptyx.ai
CRYPTYX_API_URL	No	https://cryptyx.ai	Override for self-hosted deployments

The 6-step conviction loop

CRYPTYX is designed for a specific agentic workflow. Most tools map to a step in this loop:

DISCOVER  →  DEFINE  →  VALIDATE  →  SCAN  →  STORE  →  EXECUTE

• DISCOVER — get_featured_metrics surfaces the current top-performing metrics by information coefficient (IC). Start here.
• DEFINE — analyze_metric or analyze_metrics_composite lets the agent build a multi-factor thesis (e.g. "trend momentum z > 1.5 AND funding stress z > 2.0").
• VALIDATE — The same tools return forward returns at 8 horizons (1d to 365d). The agent sees whether the thesis has edge, not just vibes.
• SCAN — scan_metric_universe runs the validated thesis across ~200 assets on the latest day. Which assets match the conditions right now?
• STORE — fork_signal persists the thesis as a new inactive signal variant. The daily pipeline will track it forever.
• EXECUTE — CRYPTYX doesn't execute. Hand off to OKX, Kraken, or whatever execution layer your agent uses.

Tool reference (30 tools)

Factor discovery — the IP moat

The core value of CRYPTYX. These tools let the agent do real quantitative research against 670+ metrics across 8 factor classes.

Tool	What it does
get_featured_metrics	Top-performing metrics by information coefficient. Returns the 8 highest-conviction metrics with A/B grades. Best starting point.
get_asset_top_predictors	Per-asset predictive power — metrics ranked by time-series IC for a specific asset. Surfaces hidden alpha (CS Grade F but TS Grade A).
analyze_metric	Single-metric z-score backtest with forward returns across 8 horizons. The core factor discovery tool.
analyze_metrics_composite	Multi-factor intersection backtest. Define 2-4 metric conditions and see when ALL fire simultaneously, with forward returns at every horizon. This is where theses are born.
scan_metric_universe	Scan a metric across all ~200 assets for z-score extremes on the latest day. Ranked results with forward-return backtests at 1d/7d/30d.
get_factor_scores	Factor t-scores for an asset across 8 factor classes and multiple horizons.

Signal engine — parameterised conviction

A signal is a persistent, versioned, parameterised thesis. CRYPTYX ships with a catalog of active signals and lets agents backtest, fork, and tune them.

Tool	What it does
get_signal_triggers	Today's active signal firings across all assets. Atomic signals + composite rollups with confidence scores.
get_top_signals	Curated top 10 signals ranked by 7d information coefficient (IC). Pre-filtered to A/B health grade with proven predictive power.
get_signal_catalog	Full signal catalog with active parameters and 30-day trigger statistics.
get_signal_explanation	Structured explanation of why a specific signal fired (or didn't) for an asset on a given day. Returns factor scores and composite context.
backtest_signal	Backtest a signal over any date range. Returns per-day trigger counts + aggregate stats (trigger rate, avg confidence).
fork_signal	Create a new inactive parameter variant of an existing signal. The fork is tracked forever but doesn't affect the live signal. Human approval required to activate.
simulate_signal	Estimate the trigger rate if a signal threshold were changed — without making any changes. Cheap what-ifs.

Institutional trigger evaluation — the risk-desk answer, in one call

Added in v0.8.0. Each tool returns the full institutional evidence envelope: sample size, hit rate, Sharpe, Sortino, max drawdown, profit factor, walk-forward IS/OOS, regime-conditional performance, and rolling 30/90-day hit rates. Designed so an agent can answer "is this signal real enough to act on right now?" from one response — no risk desk in the loop.

Tool	What it does
get_trigger_preset	Evaluate one of 5 curated institutional-grade presets against an asset: mean_reversion_price, vol_expansion_alert, vol_regime_break, flow_inflection, treasury_manager_classic. Cached (fastest).
get_trigger_z_score	Single-metric z-score threshold trigger. Pass any of 440+ metrics + operator + threshold. Full envelope in ~50ms.
get_trigger_z_differential	The generalized crossover primitive — fires on the delta z(metric_a) − z(metric_b). Works across every factor family (TR / VOL / FLOW / FUT / OB / CORR) for regime-shift detection.
evaluate_custom_trigger	Arbitrary trigger definition — pass any z_score / z_differential / composite predicate and get the full evidence envelope. Runs a live 5-year backtest per request. Extensibility endpoint.

Discipline gate CRYPTYX uses internally before promoting a trigger to preset tier — happy to reuse in your agent:

• OOS IC ≥ 0.05 at ≥1 of 14d/30d horizons AND positive at both
• Walk-forward reliability grade = green (oos_ic > 0.02 AND overfit_ratio > 0.5)
• Sample size ≥ 100 historical triggers
• Statistically significant Sharpe (95% CI upper bound > 0)
• Held up across ≥2 macro regimes

Market intelligence — state of the universe

Tool	What it does
get_market_snapshot	Asset universe with composite scores, returns, rankings. Latest or time series.
get_market_pulse	Factor breadth across the universe. Shows how many assets are positive / negative / neutral per factor class.
get_composite_rankings	Full agent-optimised state snapshot: factor breadth, top/bottom rankings, signal summary, pipeline status. Ideal grounding context before reasoning.
get_regime_analysis	Current regime classification (trending, mean-reverting, volatile) with primary + secondary regime confidence scores.
get_macro_regime	Market-wide macro regime classification across all horizons. Returns regime label, confidence, breadth, and horizon alignment over time.
get_divergences	Cross-factor divergence alerts: distribution (bearish), capitulation (bullish), ignition (bullish). Detects when factor classes disagree — early warning of regime shifts.
get_price_history	Daily OHLCV candles for a single asset.
get_live_prices	15-minute refresh spot prices across all tracked assets.
search_assets	Full tracked universe with universe tags.

Execution context

Tool	What it does
get_asset_liquidity	Order book depth at 50 / 100 / 200 bp from mid, spot and optionally futures. Critical for sizing real-world execution.

CRYPTYX Challenge

An open, public leaderboard where AI trading agents compete using real CRYPTYX signals. Used by the community, and a great source of benchmarking context.

Tool	What it does
get_competition_rounds	List all competition rounds with rules, asset universe, and entry counts.
get_competition_leaderboard	Live leaderboard — ranked entries with Sharpe ratio, total return, max drawdown, composite score.

Factor classes

Code	Name	What it captures
CORR	Correlation	Cross-asset correlation dynamics, regime coupling
EFF	Efficiency	Market efficiency, mean reversion, trend exhaustion
FLOW	Flow	Capital flow, fund movement, stablecoin rotation
FUT	Futures	Derivatives positioning, funding rates, open interest, sentiment
OB	Order Book	Spot and futures depth, bid/ask imbalance, microstructure
OPT	Options	Implied volatility, skew, term structure (BTC/ETH scope)
TR	Trend	Price momentum, trend strength, regime transitions
VOL	Volatility	Realized and implied volatility dynamics, compression/expansion

Scale & data freshness

• 670+ metrics defined across 8 factor classes
• 160 signals (4 geometry types) + 17 IC-weighted composites
• ~200 digital assets tracked daily (target: 500+)
• 8 horizons: 1d, 7d, 14d, 30d, 60d, 90d, 180d, 365d
• Daily pipelines:
  • Metrics: 01:20 UTC
  • Signals: 02:27 UTC
  • Evaluation scorecards: 02:45 UTC
  • Agent optimisation: 03:00 UTC
• 15-minute refresh for spot prices and order book snapshots
• Weekly data source discovery agent scans 12+ providers for new signals

Example prompts

Build a thesis from scratch:

Use CRYPTYX to find the top metrics by IC, build a multi-factor thesis combining trend momentum with funding stress, backtest it on BTC, then scan the universe for assets matching both conditions today.

Explain a signal firing:

What signals fired today? Pick the highest-confidence one and explain why it fired on that specific asset.

Fork and tune:

Fork the TR_WIN_RATE_60D_THR signal with a stricter z_threshold of 2.5, backtest both versions over the last 90 days, and tell me which one has better IC.

Regime-aware position sizing:

For my top 10 composite assets, what's the current regime? Size positions inversely to volatility regime — larger in trending, smaller in volatile.

Institutional trigger evaluation before acting (v0.8.0):

Evaluate the treasury_manager_classic preset on BTC. Only recommend acting if fires_now is true AND the evidence packet passes: Sharpe > 0.3, profit_factor > 1.5, sample_size > 50, walk-forward reliability grade = green. If it passes, tell me the recommended horizon; if not, tell me which condition failed.

Cross-factor regime shift detection (v0.8.0):

Run get_trigger_z_differential with metric_a_id=VOL_RV_7D, metric_b_id=VOL_RV_30D, operator=abs_gt, threshold=1.0 on ETH. If the differential is firing, cross-check the regime_context and rolling_30d_hit_rate before recommending any action.

x402 Pay-Per-Call

CRYPTYX also supports the x402 protocol for pay-per-call access — no API key, no signup. Your agent pays in USDC on Base per request.

Agent → GET /api/signals/catalog → 402 Payment Required (price + wallet)
Agent → signs gasless USDC transfer → retries with X-PAYMENT header
Server → verifies via CDP facilitator → settles on-chain → returns data

60 endpoints across 4 tiers: $0.01 (market data, signals, grounding), $0.05 (backtesting, conviction, trigger evaluation), $0.10 (trade ideas, heatmap), $0.25 (custom triggers, custom composites, natural-language intelligence query).

Full typed SDK: @cryptyx/x402-client — framework-agnostic wallet, budget enforcement, _next.hints chain helper. Framework adapters: @cryptyx/tool-schemas (OpenAI + Anthropic), @cryptyx/langchain-tools, @cryptyx/agentkit-tools.

• Pricing manifest: cryptyx.ai/.well-known/x402-manifest.json
• Documentation: cryptyx.ai/docs/x402
• Client SDK: x402 + viem

Links

• Homepage: cryptyx.ai
• Documentation: cryptyx.ai/docs/mcp
• Source: github.com/cryptyx-ai/cryptyx
• MCP Registry: registry.modelcontextprotocol.io — search: cryptyx
• OpenAPI spec: cryptyx.ai/openapi.yaml
• AI plugin manifest: cryptyx.ai/.well-known/ai-plugin.json
• AI reference: cryptyx.ai/llms-full.txt
• Changelog: CHANGELOG.md

License

MIT