ZWING KG

Endpoints (36 live)

• GET /api/search — Search the DYOR knowledge graph for crypto-related entities and results. (0.1 USDC on Base)
• GET /api/changes — Returns the latest changes and updates from the DYOR knowledge graph. (0.1 USDC on Base)
• GET /api/insights/entity/1 — Comprehensive risk and opportunity analysis for any crypto entity. Returns all active signals with full evidence across 50 signal types: smart money flows, DeFi risk, governance, token unlocks, yield anomalies, and cross-domain convergence alerts. Includes AI-synthesized narratives with actionability ratings. Free signal browsing at GET /api/insights/signals, full catalog at GET /api/signals/catalog | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (1.5 USDC on Base)
• GET /api/insights/signals/stablecoin-supply-shift — Stablecoin Supply Shift: Detects large week-over-week changes in stablecoin circulating supply (>10% with >$1M circulation). Why it matters: Stablecoin supply is a proxy for capital entering and exiting the crypto ecosystem, preceding market movements. High score: Supply change >30% — massive capital flow. Example: Stablecoin W: supply expanded +22% week-over-week ($180M increase). | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/treasury-health — Treasury Health: Analyzes protocol treasuries for concentration (>80% own tokens) and runway (non-own reserves vs operational costs). Why it matters: A treasury dominated by own tokens provides only circular value. Selling to fund operations crashes the price. High score: Own tokens >95% or runway <90 days. Example: Protocol E: 94% of $180M treasury is own tokens. Non-own reserves: $10.8M. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/insider-accumulation — Insider Accumulation / Distribution: Detects when protocol insiders — team members, early investors, and known affiliated wallets — are systematically buying or selling tokens over a rolling window. Why it matters: Insiders possess asymmetric information about protocol health. Sustained insider buying often precedes positive catalysts, while coordinated selling can signal internal concerns. High score: Large-scale directional flow (>$1M net) with strong buy/sell skew. Example: Protocol X: insider accumulation of $2.4M (47 transactions, 89% buys). | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/flow-anomaly — Daily Flow Anomaly: Statistical outlier detection on daily aggregate insider capital flows using z-scores against a 30-day rolling baseline. Why it matters: Most days are noise. This signal identifies genuinely anomalous capital movements using statistical methods. High score: Z-score >3 — a 3-sigma event. Example: April 15: anomalous net outflow of $47M (z-score=+3.2, 892 transactions). | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/convergence-alert — Convergence Alert: Detects when an entity triggers 3+ independent signal types from different analytical domains simultaneously. Why it matters: Individual signals can be noisy. Convergence from independent domains drops false positive probability dramatically. High score: 5+ signal types converging. Example: Protocol J: 4 signal types converge — insider_flow, utilization_risk, governance_apathy, yield_anomaly. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/cluster-unlock-risk — Cluster Unlock Risk: Detects when multiple tokens within the same investment cluster have simultaneous upcoming unlocks. Why it matters: Correlated unlock timing creates compounding selling pressure that simple unlock calendars miss. High score: Combined unlock >15% across a co-invested cluster. Example: Cluster 7: 4 co-invested tokens with upcoming unlocks totaling 11.2% of circulating. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/yield-anomaly — Yield Anomaly: Detects unusual APY spikes or collapses in DeFi pools, filtered to pools with >$500K TVL. Why it matters: Sudden yield changes are early warnings of incentive programs, exploits, or smart money exits. High score: APY change >500% — extreme event. Example: Pool XYZ: APY collapsed -340% in 7d (current: 2.1%, TVL: $4.2M). | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/controversial-proposal — Controversial Proposal: Detects governance proposals passing with razor-thin margins (<20% vote margin). Why it matters: Narrow margins mean nearly half the community disagrees — creating fork risk, reversal proposals, or fragmentation. High score: Margin <5% — extremely contentious, fork risk. Example: DAO Y: proposal passed with 52.3% margin (1.2M for vs 1.1M against). | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/governance-apathy — Governance Apathy: Flags governance proposals with extremely low voter turnout. Why it matters: Low participation means decisions affecting billions in TVL are made by a handful of voters, creating governance capture risk. High score: Turnout <1% — governance is effectively unguarded. Example: DAO X: proposal with only 23 voters. A $500M decision made by 23 people. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/usage-price-mismatch — Usage-Price Mismatch: Detects divergence between user growth and price movement. Why it matters: Users growing while price falls suggests undervaluation. Price rising without users suggests fragile speculative premium. High score: Users and price diverging >40%. Example: Protocol C: active users +28% but price -14% over 30d. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/exchange-liquidity-risk — Exchange Liquidity Risk: Identifies tokens available on very few exchanges (1-2) or with wide bid-ask spreads (>2%). Why it matters: Low exchange coverage means liquidity risk and deplatforming risk. Wide spreads tax every transaction. High score: Single exchange with wide spread — severe risk. Example: Token H: listed on only 1 exchange with $340K 24h volume. Spread 4.2%. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/bridge-fund — Bridge Fund Detection: Computes network centrality metrics for every fund in the investment graph, identifying funds that connect otherwise separate clusters. Why it matters: Bridge funds are kingmakers. Their investment in a new project instantly connects it to multiple existing clusters. High score: Very high betweenness centrality — connects many separate communities. Example: Fund Z: PageRank=0.0082, Betweenness=0.034. Connects 4 isolated token clusters. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• GET /api/insights/signals/whale-cross-protocol — Whale Cross-Protocol Activity: Identifies wallets with significant activity across many distinct protocols simultaneously, revealing sector-level thesis bets. Why it matters: Sophisticated actors diversify across protocols within a thesis. Tracking their cross-protocol footprint reveals emerging sector narratives. High score: Wallet active across 15+ protocols. Example: Wallet active across 18 protocols spanning DeFi lending and liquid staking sectors. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• POST /api/timeseries — Query historical crypto time-series data: token prices, market caps, TVL, protocol revenue, fees, DeFi pool APY, lending rates, stablecoin supply, and treasury balances. Data from CoinGecko, DefiLlama, TokenTerminal, and CryptoRank updated daily. Free schema at GET /api/schema lists all tables and columns | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.1 USDC on Base)
• GET /api/insights/signals/capital-efficiency — Capital Efficiency: Compares fee/revenue growth against TVL growth to identify improving or deteriorating capital efficiency. Why it matters: TVL alone is misleading. Capital efficiency reveals whether locked capital is actually productive. High score: Fee growth outpacing TVL by >50%. Example: Protocol D: fees +47% while TVL +8% over 30d. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)
• POST /api/search — Semantic search over 586K+ crypto entities — find tokens, protocols, chains, investors, and people by name or meaning. Combines exact name matching with vector similarity for fuzzy discovery. Returns URIs, labels, and similarity scores | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.1 USDC on Base)
• GET /api/insights/signals/co-investment-network — Co-Investment Network: Maps the investment graph to discover token pairs that share three or more investors. Why it matters: Shared investors create hidden correlations — common capital, common incentives, and common information flow. High score: 5+ shared investors — deeply interconnected tokens. Example: Token A and Token B share 5 investors: Fund Alpha, Fund Beta, Fund Gamma. | ZWING Intelligence (https://zwing.finance) — contact: v@zwing.finance, Telegram: @valery_zzz (0.2 USDC on Base)

+16 more endpoints.