EvolutionaryScale
EvolutionaryScale is a New York-based biology foundation model lab spun out of Meta AI's ESM team that develops AI to deepen scientific understanding of biology. Its flagship ESM3 model is a multimodal generative protein language model that reasons jointly across sequence, structure, and function, scaling to 98B parameters trained on 771B tokens from 2.78B natural proteins. The companion ESM Cambrian (ESM C) family provides protein representation learning at 300M–6B parameters as a performant ESM2 replacement. Models are accessible via the hosted Forge inference API (forge.evolutionaryscale.ai), an open-source Python SDK (`pip install esm`), open weights on Hugging Face, and AWS Marketplace (SageMaker, NVIDIA BioNeMo and NIM). EvolutionaryScale was integrated into the Biohub organization in 2025; the ESM SDK now lives at github.com/Biohub/esm.
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 EvolutionaryScale the way a machine reads it — 25 machine-readable artifacts across 7 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 — EvolutionaryScale scores 48.9/100 (developing), with a separate agent-readiness read of 48/100 (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
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile EvolutionaryScale
Each block below is one kind of artifact we hold for EvolutionaryScale. 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 7
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.
EvolutionaryScale ESM Python SDK
Official Python SDK packaging ESM3 and ESM Cambrian model loaders, the `ESMProtein` multi-track data model, generation/sampling configurations, structure tokenization utilities,...
EvolutionaryScale Embeddings API
Sequence-only tokenization and representation extraction.
EvolutionaryScale Encoding API
Tokenize ESMProtein objects into ESMProteinTensor inputs (and back).
EvolutionaryScale Generation API
Generate proteins across sequence, structure, and function tracks.
EvolutionaryScale MSA API
Fetch multiple sequence alignments used by structure predictors.
EvolutionaryScale Sampling API
Low-level forward passes with logits and sampling control.
EvolutionaryScale Structure API
Predict protein backbone coordinates from sequence and back.
Scroll within the panel for all 7 ·
Open Collections 3
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
EvolutionaryScale Forge ESM3 API
OPEN COLLECTIONEvolutionaryScale Forge ESM Cambrian API
OPEN COLLECTIONEvolutionaryScale Forge Folding API
OPEN COLLECTIONPricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Evolutionaryscale Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Evolutionaryscale Finops
FINOPSSemantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Evolutionaryscale Context
JSON-LDSpectral Rules 2
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
EvolutionaryScale API Rules
SPECTRALEvolutionaryScale API Rules
SPECTRALJSON Schema 3
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
EvolutionaryScale ESMProtein
JSON SCHEMAEvolutionaryScale GenerationConfig
JSON SCHEMAEvolutionaryScale LogitsOutput
JSON SCHEMAExamples 3
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Security 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 EvolutionaryScale — 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.
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Access & Security 2
Authentication, authorization, and security posture
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