Pyth
Pyth Network is a first-party financial oracle delivering real-time market data — 500+ price feeds spanning crypto, equities, FX, metals, rates, and commodities — to 100+ blockchains. Its pull-based Pyth Core oracle lets applications fetch signed prices from the Hermes service and verify them on-chain in a single transaction with 400ms updates, while Pyth Pro (Lazer) offers enterprise low-latency WebSocket streaming. Additional products include Entropy for on-chain randomness and Express Relay for MEV protection. Pyth exposes public REST/SSE APIs (Hermes, Benchmarks), first-party SDKs across TypeScript, Rust, Python and Solidity, a hosted MCP server, and a published agent-integration skill. Surfaced as a portfolio company of Multicoin Capital.
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.
API Evangelist profiles Pyth the way a machine reads it — 9 machine-readable artifacts across 5 APIs, 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 — Pyth scores 50.9/100 (developing), with a separate agent-readiness read of 65/100 (agent native). 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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Pyth
Each block below is one kind of artifact we hold for Pyth. 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 5
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.
Pyth Price Differences API
The Price Differences API from Pyth — 1 operation(s) for price differences.
Pyth Price Feeds API
The Price Feeds API from Pyth — 2 operation(s) for price feeds.
Pyth rest API
The rest API from Pyth — 11 operation(s) for rest.
Pyth TradingView API
Routes for TradingView Data Integration.
Pyth Updates API
The Updates API from Pyth — 2 operation(s) for updates.
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.
pyth-mcp.yml
MCP SERVERSecurity Posture 2
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.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Resources
Every other property we hold for Pyth — 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.
Get Started 4
Portal, sign-up, and the first successful call
Documentation 2
Reference material describing how the API behaves
Agent Surfaces 4
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 5
Pagination, idempotency, versioning, errors, and events
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Operate 3
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/pyth · machine-readable index on apis.io