{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp","slug":"aguskenari86-8bo7-cryptoiz-mcp","name":"cryptoiz-mcp","type":"mcp","url":"https://cryptoiz.org/McpLanding","page_url":"https://unfragile.ai/aguskenari86-8bo7-cryptoiz-mcp","categories":["mcp-servers"],"tags":["mcp","model-context-protocol","smithery:aguskenari86-8bo7/cryptoiz-mcp"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_0","uri":"capability://data.processing.analysis.whale.alpha.scanner.with.solana.dex.integration","name":"whale-alpha-scanner-with-solana-dex-integration","description":"Scans Solana DEX order books and on-chain transaction patterns to identify large whale accumulation/distribution signals in real-time. Integrates directly with Solana RPC endpoints to fetch mempool data and historical whale wallet movements, then applies proprietary scoring algorithms to surface high-conviction alpha opportunities before retail market participants.","intents":["Identify which tokens large whale wallets are accumulating on Solana DEX before price moves","Get early warning signals when whales are distributing positions to exit trades","Scan multiple token pairs simultaneously to find the highest-conviction whale alpha opportunities","Build automated trading agents that react to whale accumulation patterns"],"best_for":["Solana traders and quants building whale-tracking bots","Crypto hedge funds automating alpha discovery workflows","Solo developers building LLM agents for on-chain analysis"],"limitations":["Solana-only — no support for Ethereum, Polygon, or other chains","Real-time scanning introduces ~500ms latency due to RPC node query time","Whale detection heuristics may produce false positives during low-liquidity periods","Requires continuous API calls to maintain fresh signals — no built-in caching layer"],"requires":["MCP client compatible with Smithery registry","USDC balance for pay-per-call x402 Dexter integration","Solana RPC endpoint (public or private)","Active Solana wallet for gas sponsorship verification"],"input_types":["token_mint_address (string)","time_window (integer, seconds)","min_whale_threshold (float, SOL amount)"],"output_types":["structured JSON with whale wallet addresses, accumulation scores, transaction hashes, timestamp"],"categories":["data-processing-analysis","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_1","uri":"capability://data.processing.analysis.divergence.pattern.detection.hidden.breakout.classic","name":"divergence-pattern-detection-hidden-breakout-classic","description":"Analyzes token price action and volume patterns to detect three types of technical divergences: hidden divergence (continuation signals), breakout divergence (reversal setup), and classic divergence (momentum exhaustion). Uses candlestick OHLCV data from Solana DEX to compute RSI/MACD indicators and identify price-momentum misalignments that precede directional moves.","intents":["Detect hidden divergences that signal continuation of existing trends before breakouts occur","Identify classic divergences indicating momentum exhaustion and potential reversals","Find breakout divergence setups that precede significant price moves","Automate divergence scanning across multiple token pairs to filter for high-probability setups"],"best_for":["Technical traders automating divergence detection workflows","Quant teams building multi-timeframe analysis agents","LLM-powered trading bots that need structured technical signals"],"limitations":["Requires minimum 50+ candles of historical data per token — unreliable for newly-listed tokens","Divergence signals lag by 1-2 candles due to indicator calculation overhead","False positive rate increases during low-volume periods or flash crashes","No multi-timeframe correlation — each timeframe analyzed independently"],"requires":["MCP client with x402 Dexter payment integration","USDC balance ($0.04 per call)","Solana DEX OHLCV data source (via RPC or indexer)","Minimum 1-hour historical price data per token"],"input_types":["token_mint_address (string)","timeframe (enum: 1m, 5m, 15m, 1h, 4h, 1d)","divergence_type (enum: hidden, breakout, classic)"],"output_types":["structured JSON with divergence type, price levels, indicator values, confidence score, entry/exit zones"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_2","uri":"capability://data.processing.analysis.accumulation.phase.scoring.with.whale.behavior.analysis","name":"accumulation-phase-scoring-with-whale-behavior-analysis","description":"Scores tokens on a 0-100 scale based on whale accumulation behavior patterns: large wallet inflows, decreasing sell pressure, increasing buy volume concentration. Analyzes on-chain wallet movements and DEX order flow to determine if whales are actively accumulating positions, outputting a quantified accumulation phase score that feeds into trading decision systems.","intents":["Quantify how aggressively whales are accumulating a specific token on a 0-100 scale","Filter token lists to find only those in active accumulation phases","Track accumulation score changes over time to detect when whales shift from accumulation to distribution","Build automated trading systems that only enter positions during high accumulation scores"],"best_for":["Quantitative traders building systematic entry/exit rules based on whale behavior","Crypto hedge funds automating portfolio construction around accumulation phases","LLM agents that need to reason about market microstructure and whale positioning"],"limitations":["Accumulation scoring is backward-looking — detects past whale behavior, not future intent","Score can lag 5-15 minutes behind actual whale accumulation due to RPC query batching","Whale wallet identification relies on heuristics (large balance + frequent trading) — may misclassify smart contract addresses","No cross-chain whale tracking — only detects accumulation on Solana DEX"],"requires":["MCP client with x402 Dexter integration","USDC balance ($0.03 per call)","Solana RPC endpoint for wallet balance queries","Historical on-chain transaction data (minimum 7 days)"],"input_types":["token_mint_address (string)","lookback_period (integer, hours)","whale_threshold (float, SOL amount)"],"output_types":["structured JSON with accumulation_score (0-100), whale_wallet_count, inflow_volume, buy_pressure_ratio, confidence_level"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_3","uri":"capability://data.processing.analysis.neutral.phase.detection.for.consolidation.periods","name":"neutral-phase-detection-for-consolidation-periods","description":"Identifies tokens in neutral consolidation phases where whale activity is balanced (neither accumulating nor distributing) and price action is range-bound. Uses on-chain volume distribution, order book depth analysis, and wallet movement patterns to detect equilibrium periods that often precede directional breakouts.","intents":["Identify tokens in consolidation phases to avoid false breakout trades","Find neutral-phase tokens that are likely to breakout soon after consolidation ends","Build trading systems that wait for neutral phase confirmation before entering positions","Detect when tokens transition from neutral to accumulation/distribution phases"],"best_for":["Swing traders waiting for consolidation breakouts","Systematic traders that need to filter out choppy, range-bound markets","LLM agents that need to understand market microstructure and equilibrium states"],"limitations":["Neutral phase detection is subjective — threshold for 'balanced' whale activity is configurable but may not match trader intuition","Consolidation periods can last hours to days — signal is not useful for intraday scalpers","False positives during low-volume periods where whale activity appears balanced due to lack of data","No prediction of breakout direction — only identifies that consolidation is likely to end"],"requires":["MCP client with x402 Dexter integration","USDC balance ($0.03 per call)","Solana RPC endpoint for order book depth queries","Minimum 24 hours of historical price and volume data"],"input_types":["token_mint_address (string)","lookback_period (integer, hours)","balance_threshold (float, 0-1 ratio)"],"output_types":["structured JSON with neutral_phase_score (0-100), buy_sell_ratio, order_book_imbalance, consolidation_duration, breakout_probability"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_4","uri":"capability://data.processing.analysis.distribution.phase.scoring.with.exit.signal.detection","name":"distribution-phase-scoring-with-exit-signal-detection","description":"Scores tokens on a 0-100 scale based on whale distribution behavior: large wallet outflows, increasing sell pressure, decreasing buy volume concentration. Analyzes on-chain wallet movements and DEX order flow to determine if whales are actively exiting positions, outputting a quantified distribution phase score that signals when to reduce exposure.","intents":["Quantify how aggressively whales are distributing/exiting positions on a 0-100 scale","Get early warning when whale accumulation is ending and distribution is beginning","Build automated stop-loss or position-reduction rules triggered by rising distribution scores","Identify tokens where whale exits are creating selling pressure before retail panic selling"],"best_for":["Risk-averse traders that want to exit before whale distribution accelerates","Systematic traders building automated position management rules","Crypto funds managing portfolio risk through whale behavior monitoring"],"limitations":["Distribution score is backward-looking — detects past whale exits, not future selling","Score can lag 5-15 minutes behind actual whale distribution due to RPC query batching","Whale wallet identification relies on heuristics — may misclassify smart contract addresses or MEV bots","High distribution scores don't guarantee price decline — whales may be rebalancing, not exiting"],"requires":["MCP client with x402 Dexter integration","USDC balance ($0.04 per call)","Solana RPC endpoint for wallet balance and transaction queries","Historical on-chain transaction data (minimum 7 days)"],"input_types":["token_mint_address (string)","lookback_period (integer, hours)","whale_threshold (float, SOL amount)"],"output_types":["structured JSON with distribution_score (0-100), whale_wallet_count, outflow_volume, sell_pressure_ratio, exit_confidence_level"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_5","uri":"capability://data.processing.analysis.btc.macro.regime.detection.for.altcoin.correlation","name":"btc-macro-regime-detection-for-altcoin-correlation","description":"Analyzes Bitcoin price action, volatility regime, and trend direction to classify the current macro market regime (bull/bear/consolidation) and outputs a regime score that correlates with altcoin performance. Uses BTC OHLCV data, volatility indicators, and trend analysis to provide macro context for Solana token trading decisions.","intents":["Determine if current BTC regime is favorable for altcoin trading (bull vs bear vs choppy)","Adjust trading strategy aggressiveness based on BTC macro regime classification","Build LLM agents that understand macro context before making token-level trading decisions","Filter out altcoin trades during unfavorable BTC regimes to reduce drawdowns"],"best_for":["Altcoin traders that want to trade with BTC macro context","Systematic traders building regime-aware portfolio allocation systems","LLM agents that need to understand macro crypto market conditions"],"limitations":["BTC regime classification is lagging — detects regime changes 1-2 days after they occur","Altcoin correlation with BTC varies by token — regime score is not universally predictive","No forward-looking regime prediction — only classifies current regime based on historical data","Regime transitions can be ambiguous — consolidation periods may be misclassified as early bull/bear"],"requires":["MCP client with x402 Dexter integration","USDC balance ($0.02 per call)","BTC OHLCV data source (via CoinGecko, Binance, or other exchange API)","Minimum 90 days of historical BTC price data"],"input_types":["timeframe (enum: 1h, 4h, 1d, 1w)","lookback_period (integer, days)"],"output_types":["structured JSON with regime_type (bull/bear/consolidation), regime_score (0-100), volatility_level, trend_direction, altcoin_correlation_strength"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_6","uri":"capability://data.processing.analysis.btc.futures.signal.generation.with.leverage.context","name":"btc-futures-signal-generation-with-leverage-context","description":"Analyzes Bitcoin futures market data (funding rates, open interest, liquidation levels) to generate trading signals that indicate directional bias and leverage extremes. Detects when futures markets are overextended (high funding rates, extreme open interest) and generates signals for mean-reversion trades or trend continuation based on market structure.","intents":["Identify when BTC futures markets are overheated with excessive leverage (high funding rates)","Get signals for mean-reversion trades when futures funding reaches extremes","Understand liquidation levels and open interest to assess market structure","Build LLM agents that understand futures market extremes before making spot trading decisions"],"best_for":["Futures traders looking for leverage extremes and mean-reversion opportunities","Spot traders that want to avoid trading against overlevered futures markets","Systematic traders building multi-market correlation strategies (spot + futures)"],"limitations":["Futures signals are most reliable during extreme leverage periods — less useful in normal market conditions","Funding rate extremes can persist for hours or days — signal timing is imprecise","Liquidation cascades are difficult to predict — liquidation levels change as price moves","Requires real-time futures data — lagged data reduces signal quality significantly"],"requires":["MCP client with x402 Dexter integration","USDC balance ($0.06 per call)","Real-time BTC futures data source (Binance, Bybit, or other exchange API)","Minimum 7 days of historical funding rate and open interest data"],"input_types":["exchange (enum: binance, bybit, dydx)","timeframe (enum: 1h, 4h, 1d)","signal_type (enum: funding_extreme, liquidation_level, oi_trend)"],"output_types":["structured JSON with signal_type, signal_strength (0-100), funding_rate, open_interest, liquidation_levels, mean_reversion_probability"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_7","uri":"capability://tool.use.integration.mcp.protocol.integration.with.x402.dexter.payment.gateway","name":"mcp-protocol-integration-with-x402-dexter-payment-gateway","description":"Integrates CryptoIZ tools into the Model Context Protocol (MCP) ecosystem via Smithery registry, enabling LLM agents and AI applications to call whale intelligence functions directly. Uses x402 Dexter payment gateway to handle USDC micropayments per API call with gas sponsorship, eliminating need for SOL and enabling serverless, pay-as-you-go pricing model.","intents":["Enable Claude, GPT-4, and other LLMs to call CryptoIZ whale intelligence tools natively","Build autonomous AI agents that make trading decisions based on real-time whale data","Integrate whale intelligence into existing MCP-compatible applications without custom API wrappers","Pay for API calls in USDC without managing SOL gas fees or wallet complexity"],"best_for":["AI/LLM developers building autonomous trading agents","Non-technical founders prototyping crypto trading bots with Claude or GPT-4","Teams migrating from REST APIs to MCP-based tool ecosystems"],"limitations":["MCP protocol overhead adds ~100-200ms latency per tool call compared to direct REST API","x402 Dexter payment integration requires USDC balance — no credit card or fiat on-ramp","Tool calling context window is limited by LLM context size — cannot call tools with very large output payloads","No built-in rate limiting or quota management — requires external monitoring for cost control"],"requires":["MCP-compatible client (Claude Desktop, Cursor, or custom MCP implementation)","Solana wallet with USDC balance for x402 Dexter payments","Installation via agentcash: npx agentcash add https://mcp.cryptoiz.org","LLM with native tool-calling support (Claude 3+, GPT-4, etc.)"],"input_types":["MCP tool call with JSON parameters"],"output_types":["structured JSON response with tool results"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_8","uri":"capability://data.processing.analysis.real.time.whale.wallet.tracking.with.transaction.history","name":"real-time-whale-wallet-tracking-with-transaction-history","description":"Maintains a real-time index of identified whale wallets on Solana and tracks their transaction history, balance changes, and trading patterns. Queries Solana RPC to fetch wallet movements and cross-references with DEX transaction logs to build a historical profile of whale behavior that informs accumulation/distribution scoring.","intents":["Track specific whale wallet addresses and their trading activity over time","Build historical profiles of whale behavior to identify patterns and predict future moves","Get alerts when tracked whale wallets make large transactions","Analyze whale wallet composition and diversification to understand market positioning"],"best_for":["Traders that want to follow specific whale wallets","Quant teams building whale behavior prediction models","LLM agents that need to reason about specific whale wallet history"],"limitations":["Whale wallet identification is heuristic-based — may include smart contracts or MEV bots","Transaction history indexing has ~5-15 minute lag due to RPC query batching","No cross-chain whale tracking — only Solana wallets are tracked","Wallet privacy concerns — tracking whale wallets may enable front-running or MEV attacks"],"requires":["MCP client with x402 Dexter integration","USDC balance for per-call pricing","Solana RPC endpoint with transaction history support","Minimum 7 days of historical transaction data per whale"],"input_types":["whale_wallet_address (string, Solana public key)","lookback_period (integer, days)"],"output_types":["structured JSON with wallet_address, balance, transaction_history, trading_patterns, token_holdings, average_trade_size"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"smithery_aguskenari86-8bo7-cryptoiz-mcp__cap_9","uri":"capability://data.processing.analysis.multi.token.batch.scanning.with.parallel.execution","name":"multi-token-batch-scanning-with-parallel-execution","description":"Enables batch scanning of multiple token pairs simultaneously using parallel RPC queries and result aggregation. Accepts a list of token mint addresses and returns whale alpha, divergence, and phase scores for all tokens in a single call, reducing latency and cost compared to sequential per-token queries.","intents":["Scan entire token watchlists (50+ tokens) in seconds to find highest-conviction opportunities","Build daily/hourly reports of whale activity across multiple tokens","Create filtered token lists based on combined accumulation + divergence + regime scores","Reduce API call costs by batching multiple tokens into single requests"],"best_for":["Traders managing large watchlists (50+ tokens)","Quant teams building daily alpha reports","LLM agents that need to scan token universes before making decisions"],"limitations":["Batch size is limited by RPC node rate limits — typically 50-100 tokens per batch","Parallel execution adds complexity to result aggregation and error handling","Cost savings are modest (10-20%) compared to sequential calls due to fixed overhead","Batch results are less fresh than individual queries due to aggregation time"],"requires":["MCP client with x402 Dexter integration","USDC balance for batch pricing (typically 0.8x per-token rate)","Solana RPC endpoint with high rate limits","List of valid Solana token mint addresses"],"input_types":["token_mint_addresses (array of strings)","analysis_types (array of enums: whale_alpha, divergence, accumulation, neutral, distribution, btc_regime, btc_futures)"],"output_types":["structured JSON array with results for each token, including all requested analysis types"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":50,"verified":false,"data_access_risk":"moderate","permissions":["MCP client compatible with Smithery registry","USDC balance for pay-per-call x402 Dexter integration","Solana RPC endpoint (public or private)","Active Solana wallet for gas sponsorship verification","MCP client with x402 Dexter payment integration","USDC balance ($0.04 per call)","Solana DEX OHLCV data source (via RPC or indexer)","Minimum 1-hour historical price data per token","MCP client with x402 Dexter integration","USDC balance ($0.03 per call)"],"failure_modes":["Solana-only — no support for Ethereum, Polygon, or other chains","Real-time scanning introduces ~500ms latency due to RPC node query time","Whale detection heuristics may produce false positives during low-liquidity periods","Requires continuous API calls to maintain fresh signals — no built-in caching layer","Requires minimum 50+ candles of historical data per token — unreliable for newly-listed tokens","Divergence signals lag by 1-2 candles due to indicator calculation overhead","False positive rate increases during low-volume periods or flash crashes","No multi-timeframe correlation — each timeframe analyzed independently","Accumulation scoring is backward-looking — detects past whale behavior, not future intent","Score can lag 5-15 minutes behind actual whale accumulation due to RPC query batching","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7573560910145041,"quality":0.55,"ecosystem":0.38999999999999996,"match_graph":0.25,"freshness":0.5,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:25.062Z","last_scraped_at":"2026-05-03T15:18:25.566Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=aguskenari86-8bo7-cryptoiz-mcp","compare_url":"https://unfragile.ai/compare?artifact=aguskenari86-8bo7-cryptoiz-mcp"}},"signature":"pAv9Q7HkbNxAJfudCwtDkFJ41IZEoEXQjvtrrJ0emvu1IG+2WvvzxikIWPKzaEZGe1GdSLiCo4aeVurN8QmNCw==","signedAt":"2026-06-20T17:47:13.304Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/aguskenari86-8bo7-cryptoiz-mcp","artifact":"https://unfragile.ai/aguskenari86-8bo7-cryptoiz-mcp","verify":"https://unfragile.ai/api/v1/verify?slug=aguskenari86-8bo7-cryptoiz-mcp","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}