Ginkgo Bioworks

Ginkgo Bioworks is a synthetic biology company operating autonomous labs and a horizontal platform for engineering biology. Its public developer surface is the Ginkgo AI Model API (api.ginkgobioworks.ai), which runs inference on public and Ginkgo-proprietary biological foundation models — protein and DNA masked language models and embedding models such as ESM2 (650M/3B), ginkgo-aa0-650M, and ginkgo-maskedlm-3utr-v1. The API is an async, job-polling REST service: callers POST a transform request, receive a job result URL, and poll until the job completes. Authentication is via an x-api-key header, credits and keys are issued from the models portal, and an official Python client (ginkgo-ai-client) is published to PyPI. Ginkgo was surfaced as a Felicis portfolio company and enriched into the API Evangelist network.

Ginkgo Bioworks publishes 1 API on the APIs.io network. Tagged areas include Company, Synthetic Biology, Biotechnology, Artificial Intelligence, and Machine Learning.

Ginkgo Bioworks’ developer surface includes documentation, API reference, getting-started guide, signup flow, authentication, and 11 more developer resources.

🌐 Visit website 📡 Source on GitHub

24.8/100 emerging ▬ flat Agent 29/100 agent aware Full breakdown ↓
scored 2026-07-27 · rubric v0.5

AccessSelf serve

1 APIs 1 MCP Servers

CompanySynthetic BiologyBiotechnologyArtificial IntelligenceMachine LearningProtein ModelsBioinformaticsInference API

Kin Score

Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5

Composite quality — 24.8/100 · emerging

Contract Quality 0.0 / 25

Developer Ergonomics 12.2 / 20

Commercial Clarity 2.6 / 20

Operational Transparency 0.7 / 13

Governance 0.0 / 12

Discoverability 9.3 / 10

Agent readiness — 29/100 · agent aware

Machine-Readable Contract 0 / 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 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/ginkgo: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 1

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

Ginkgo AI Model API

Async, job-polling REST API for running inference on public and Ginkgo-proprietary biological foundation models — protein/DNA masked language modeling and mean-embedding generat...

MCP Servers 1

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

Get Started 3

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

SignUp

SignUp

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

LLMsTxt

LLMsTxt

Design & Contract 3

Pagination, idempotency, versioning, errors, and events

Conventions

Conventions

ErrorCatalog

ErrorCatalog

Lifecycle

Lifecycle

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

SDKs

SDKs

Access & Security 2

Authentication, authorization, and security posture

Authentication

Authentication

DomainSecurity

DomainSecurity

Company 1

The organization behind the API

Website

Website

Source (apis.yml)

aid: ginkgo
name: Ginkgo Bioworks
description: 'Ginkgo Bioworks is a synthetic biology company operating autonomous labs and a horizontal platform for engineering
  biology. Its public developer surface is the Ginkgo AI Model API (api.ginkgobioworks.ai), which runs inference on public
  and Ginkgo-proprietary biological foundation models — protein and DNA masked language models and embedding models such as
  ESM2 (650M/3B), ginkgo-aa0-650M, and ginkgo-maskedlm-3utr-v1. The API is an async, job-polling REST service: callers POST
  a transform request, receive a job result URL, and poll until the job completes. Authentication is via an x-api-key header,
  credits and keys are issued from the models portal, and an official Python client (ginkgo-ai-client) is published to PyPI.
  Ginkgo was surfaced as a Felicis portfolio company and enriched into the API Evangelist network.'
url: https://raw.githubusercontent.com/api-evangelist/ginkgo/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- felicis
x-tier: stub
x-tier-reason: portfolio-lead
accessModel:
  pricing: unknown
  onboarding: self-serve
  trial: false
  try_now: false
  public: false
  label: Self-serve signup
  confidence: medium
  source:
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://www.ginkgobioworks.com/favicon.ico
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Synthetic Biology
- Biotechnology
- Artificial Intelligence
- Machine Learning
- Protein Models
- Bioinformatics
- Inference API
apis:
- name: Ginkgo AI Model API
  description: Async, job-polling REST API for running inference on public and Ginkgo-proprietary biological foundation models
    — protein/DNA masked language modeling and mean-embedding generation. Authenticated with an x-api-key header; an official
    Python client is published on PyPI.
  humanURL: https://ginkgobioworks.github.io/ginkgo-ai-client/
  baseURL: https://api.ginkgobioworks.ai/v1
  tags:
  - Artificial Intelligence
  - Protein Models
  - Inference API
  properties:
  - type: Documentation
    url: https://ginkgobioworks.github.io/ginkgo-ai-client/
  - type: Authentication
    url: authentication/ginkgo-authentication.yml
  - type: Conventions
    url: conventions/ginkgo-conventions.yml
  - type: ErrorCatalog
    url: errors/ginkgo-error-codes.yml
  - type: Lifecycle
    url: lifecycle/ginkgo-lifecycle.yml
  - type: MCPServer
    url: mcp/ginkgo-mcp.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.ginkgobioworks.com
- type: DeveloperPortal
  url: https://ginkgobioworks.github.io/ginkgo-ai-client/
- type: Documentation
  url: https://ginkgobioworks.github.io/ginkgo-ai-client/
- type: APIReference
  url: https://ginkgobioworks.github.io/ginkgo-ai-client/api_reference.html
- type: GettingStarted
  url: https://ginkgobioworks.github.io/ginkgo-ai-client/
- type: SignUp
  url: https://models.ginkgobioworks.ai/
- type: GitHubOrganization
  url: https://github.com/ginkgobioworks
- type: Packages
  url: packages/ginkgo-packages.yml
- type: SDKs
  url: packages/ginkgo-packages.yml
- type: Authentication
  url: authentication/ginkgo-authentication.yml
- type: Conventions
  url: conventions/ginkgo-conventions.yml
- type: ErrorCatalog
  url: errors/ginkgo-error-codes.yml
- type: Lifecycle
  url: lifecycle/ginkgo-lifecycle.yml
- type: MCPServer
  url: mcp/ginkgo-mcp.yml
- type: DomainSecurity
  url: security/ginkgo-domain-security.yml
- type: LLMsTxt
  url: llms/ginkgo-llms.txt
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence