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Merkle Science

Merkle Science is a blockchain analytics and predictive crypto risk platform that helps virtual asset businesses, financial institutions, and government agencies detect fraud, monitor transactions, and stay compliant with AML, KYC, and CFT regulations across 10,000+ crypto assets. Its product suite includes Compass (transaction and wallet monitoring), Tracker (forensic investigation and fund tracing), KYBB / Know Your Blockchain Business (counterparty due diligence and risk intelligence), Onchain Pulse (ecosystem monitoring and token risk scoring), and Institute (compliance training and certification). The public KYBB API exposes off-chain VASP due-diligence data — KYC/AML posture, supported coins and FIAT, permitted activities, regulatory alerts, licensing and legal-entity records, and jurisdictional restrictions. Merkle Science is backed by 500 Global.

agent ready

Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.

Kin Score

API Evangelist profiles Merkle Science the way a machine reads it — 5 machine-readable artifacts across 1 API, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Merkle Science scores 50.6/100 (developing), with a separate agent-readiness read of 55/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 50.6/100 · developing
Contract Quality 15.9 / 25
Developer Ergonomics 14.8 / 20
Commercial Clarity 10.0 / 20
Operational Transparency 0.7 / 13
Governance 0.0 / 12
Discoverability 9.3 / 10
Agent readiness — 55/100 · agent ready
Machine-Readable Contract 18 / 18
Agentic Access Contract 0 / 15
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 8 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 5 / 5
Well-Known Catalog 4 / 4
Consent & Bot Identity 0 / 3

How we profile Merkle Science

Each block below is one kind of artifact we hold for Merkle Science. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

APIs 1

Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.

Individual APIs this provider publishes, each with its own machine-readable definition.

Merkle Science VASP Entities API

Query and retrieve off-chain VASP due-diligence entities.

MCP Servers 1

Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.

Model Context Protocol servers that expose these APIs to AI agents.

Security Posture 3

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Merkle Science Authentication

apiKey · 1 scheme

SECURITY

Merkle Science Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Merkle Science Trust Center

SOC 2, ISO 27001, GDPR

SECURITY

Resources

Every other property we hold for Merkle Science — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Documentation 2

Reference material describing how the API behaves

Agent Surfaces 4

MCP servers, agent skills, and machine-readable catalogs

Build 1

SDKs, sample code, and the tooling you integrate with

Operate 1

Status, limits, changes, and where to get help

Commercial 2

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

← All providers · Data indexed from github.com/api-evangelist/merkle-science · machine-readable index on apis.io