Domino Data Lab

Domino Data Lab is an enterprise MLOps and AI platform used by data science and machine learning teams to build, deploy, monitor, and govern models and data-science applications across hybrid and multi-cloud infrastructure. The platform exposes a REST Platform API (apps, projects, model serving, environments, workspaces, cost, users/orgs, extensions, and data sources), a separate Domino Data API for data access, and a Model Monitoring API, alongside official Python (python-domino) and R clients, a VS Code extension, and an official Model Context Protocol server distributed through its Claude Code plugin. Originally surfaced as a portfolio company of bloomberg-beta and enriched from its public developer surface.

Domino Data Lab is listed with 1 API on the APIs.io network. Tagged areas include Company, MLOps, Data Science, Machine Learning, and AI Platform.

Domino Data Lab’s developer surface includes CLI, changelog, support, documentation, API reference, getting-started guide, engineering blog, and 24 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

35.9/100 thin ▲ 6.6 Agent 19/100 agent aware Front door AI 6/6 dominant saas Full breakdown ↓
scored 2026-10-17 · rubric v0.24.0

1 API 1 MCP Servers

Company MLOps Data Science Machine Learning AI Platform Model Monitoring Enterprise AI

Kin Score

Kin Score How this is scored →
scored 2026-10-17 · rubric v0.24.0

Composite quality — 35.9/100 · thin

Contract Quality 0.0 / 21

Developer Ergonomics 12.5 / 17

Access Clarity 8.1 / 17

Operational Transparency 2.0 / 11

Contract Governance 1.9 / 10

Discoverability 5.4 / 9

Regulatory Posture 3.0 / 15

Agent readiness — 19/100 · agent aware

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 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

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 6 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 6 / 6

Agentic Commerce Well-Known Document 0 / 5

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/domino-data-lab: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
MLOps and AI/ML Infrastructure (LF AI & Data, MLPerf, Kubeflow)	undeclared	-	-	1

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

APIs 1

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

Domino Platform API

REST Platform API exposing apps, projects, model serving, environments, workspaces, cost, users, orgs, extensions, and data sources.

MCP Servers 1

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

Domino Data Lab MCP Server

Local (stdio) MCP server; 4 tools listed.

MCP SERVER

Pricing Plans 1

Published pricing tiers and plan structures.

Domino Data Lab Plans Pricing

3 plans

PLANS

Security Posture 3

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

Domino Data Lab Authentication

apiKey · 1 scheme

SECURITY

Domino Data Lab Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Domino Data Lab Trust Center

SOC 2, ISO 27001

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

WellKnown

WellKnown

MCPServer

MCPServer

LLMsTxt

LLMsTxt

Design & Contract 2

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Conventions

Conventions

Build 5

SDKs, sample code, and the tooling you integrate with

CLI

CLI

GitHubOrganization

Postman

Packages

SDKs

Access & Security 4

Authentication, authorization, and security posture

Compliance

TrustCenter

Authentication

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

ChangeLog

ChangeLog

Support

Support

ChangeLog

ChangeLog

Commercial 4

Pricing, plans, and the legal terms of use

Plans

Pricing

TermsOfService

PrivacyPolicy

Company 3

The organization behind the API

BlogRSS

BlogRSS

Website

Website

Blog

Blog

Other 3

Properties that don't map to a standard resource type

AgentCard

AgentCard

Hosts

Hosts

Vendors

Vendors

Source (apis.yml)

aid: domino-data-lab
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - authentication
  - security
  generated: '2026-09-03'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/domino-data-lab.png
name: Domino Data Lab
description: Domino Data Lab is an enterprise MLOps and AI platform used by data science and machine learning teams to build,
  deploy, monitor, and govern models and data-science applications across hybrid and multi-cloud infrastructure. The platform
  exposes a REST Platform API (apps, projects, model serving, environments, workspaces, cost, users/orgs, extensions, and
  data sources), a separate Domino Data API for data access, and a Model Monitoring API, alongside official Python (python-domino)
  and R clients, a VS Code extension, and an official Model Context Protocol server distributed through its Claude Code plugin.
  Originally surfaced as a portfolio company of bloomberg-beta and enriched from its public developer surface.
url: https://raw.githubusercontent.com/api-evangelist/domino-data-lab/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- bloomberg-beta
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
tags:
- Company
- MLOps
- Data Science
- Machine Learning
- AI Platform
- Model Monitoring
- Enterprise AI
tags_raw:
- Company
- MLOps
- Data Science
- Machine Learning
- AI Platform
- Model Monitoring
- Enterprise AI
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Plans
  url: plans/domino-data-lab-plans-pricing.yml
- url: https://domino.ai/feed.xml
  type: BlogRSS
- type: CLI
  url: cli/domino-data-lab-cli.yml
- type: ChangeLog
  url: changelog/domino-data-lab-changelog.yml
- type: Compliance
  url: https://trust.domino.ai/
- type: Conformance
  url: conformance/domino-data-lab-conformance.yml
- type: AgentCard
  url: a2a/domino-data-lab-a2a.yml
- type: WellKnown
  url: well-known/domino-data-lab-well-known.yml
- type: Hosts
  url: hosts/domino-data-lab-hosts.yml
- type: Vendors
  url: vendors/domino-data-lab-vendors.yml
- type: Support
  url: https://support.domino.ai/support/s/
- type: ChangeLog
  url: https://docs.domino.ai/release-notes/cloud-release
- type: TrustCenter
  url: security/domino-data-lab-trust-center.yml
- type: Website
  url: https://domino.ai/
- type: DeveloperPortal
  url: https://docs.dominodatalab.com/
- type: Documentation
  url: https://docs.dominodatalab.com/
- type: APIReference
  url: https://docs.dominodatalab.com/en/cloud/api_guide/8c929e/domino-platform-api-reference/
- type: GettingStarted
  url: https://docs.dominodatalab.com/en/cloud/api_guide/f35c19/api-guide/
- type: Blog
  url: https://domino.ai/blog
- type: GitHubOrganization
  url: https://github.com/dominodatalab
- type: Pricing
  url: https://domino.ai/pricing
- type: TermsOfService
  url: https://domino.ai/legal/terms
- type: PrivacyPolicy
  url: https://domino.ai/legal/privacy-policy
- type: Postman
  url: https://www.postman.com/dominodatalab/workspace
- type: Authentication
  url: authentication/domino-data-lab-authentication.yml
- type: Packages
  url: packages/domino-data-lab-packages.yml
- type: SDKs
  url: packages/domino-data-lab-packages.yml
- type: MCPServer
  url: mcp/domino-data-lab-mcp.yml
- type: Conventions
  url: conventions/domino-data-lab-conventions.yml
- type: LLMsTxt
  url: llms/domino-data-lab-llms.txt
- type: DomainSecurity
  url: security/domino-data-lab-domain-security.yml
apis:
- name: Domino Platform API
  description: REST Platform API exposing apps, projects, model serving, environments, workspaces, cost, users, orgs, extensions,
    and data sources.
  humanURL: https://docs.dominodatalab.com/en/cloud/api_guide/8c929e/domino-platform-api-reference/
  baseURL: null
  aid: domino-data-lab:domino-platform-api
x-coverage:
  state: unreadable
  reason: no-machine-readable-spec
  detail: The provider's documentation pages are HTML without a published OpenAPI, AsyncAPI, GraphQL, gRPC, or WSDL contract.
  evidence:
  - url: https://docs.dominodatalab.com/en/cloud/api_guide/8c929e/domino-platform-api-reference/
    status: 200
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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