dbt
dbt Labs operates dbt Cloud, the managed platform for the open-source dbt (data build tool) used to transform data inside cloud warehouses. dbt Cloud exposes a set of APIs for managing accounts, projects, jobs, and runs programmatically (Administrative API), inspecting project metadata (Discovery API), and querying governed metrics (Semantic Layer API).
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles dbt the way a machine reads it — 39 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 — dbt scores 63.8/100 (strong), 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.
How we profile dbt
Each block below is one kind of artifact we hold for dbt. 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.
dbt Accounts API
The Accounts API from dbt — 1 operation(s) for accounts.
dbt Environments API
The Environments API from dbt — 1 operation(s) for environments.
dbt Jobs API
The Jobs API from dbt — 1 operation(s) for jobs.
dbt Metadata API
The Metadata API from dbt — 1 operation(s) for metadata.
dbt Metrics API
The Metrics API from dbt — 1 operation(s) for metrics.
dbt Projects API
The Projects API from dbt — 2 operation(s) for projects.
dbt Runs API
The Runs API from dbt — 4 operation(s) for runs.
Scroll within the panel for all 7 ·
Postman Collections 3
A runnable collection turns the contract into something a developer can execute in seconds. We profile them because the fastest way to trust an API is to make a real call against it.
Ready-to-run Postman collections for exercising this provider's APIs.
dbt Cloud Administrative API
POSTMANdbt Cloud Discovery API
POSTMANdbt Cloud Semantic Layer API
POSTMANOpen 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).
dbt Cloud Administrative API
OPEN COLLECTIONdbt Cloud Discovery API
OPEN COLLECTIONdbt Cloud Semantic Layer API
OPEN COLLECTIONArazzo Workflows 13
Real integrations are rarely a single call. Arazzo describes the multi-step sequences — auth, then create, then confirm — so both a human and an agent can follow the choreography, not just the endpoints.
Multi-step API workflows described with the Arazzo specification.
dbt Cloud Account, Project and Job Inventory
Walk from the first account to its projects to its jobs to build a hierarchy snapshot.
ARAZZOdbt Cloud Bootstrap From Account to First Run
Resolve account, project and environment, create a job, and trigger its first run.
ARAZZOdbt Cloud Create Job and Run It
Create a new job in a project environment, then immediately trigger a run of it.
ARAZZOdbt Cloud Create, Run, Poll and Collect Artifacts
Create a job, trigger it, poll the run to success (status 10), and list artifacts.
ARAZZOdbt Cloud Environment-Scoped Job Run
Pick an environment, create a job in it, and trigger the job's first run.
ARAZZOdbt Cloud Find Job and Trigger Run
List jobs in an account, fetch the job's configuration, then trigger a run of it.
ARAZZOdbt Cloud Job Run History and Latest Artifacts
List runs, read the most recent run, and fetch its artifacts when it succeeded.
ARAZZOdbt Cloud Provision a Job in a Project Environment
Resolve a project and one of its environments, then create a job bound to both.
ARAZZOdbt Cloud Re-run the Latest Failed Run
Inspect the most recent run, and if it failed, re-trigger its job.
ARAZZOdbt Cloud Get Run and Fetch Its Artifacts
Read a run, branch on whether it succeeded, and list its artifacts only on success.
ARAZZOdbt Cloud Run Completion to Metadata Discovery
Confirm a run succeeded, then query the Discovery API for the models it produced.
ARAZZOdbt Cloud Run Completion to Semantic Layer Metrics
Confirm a run succeeded, then query the Semantic Layer API for available metrics.
ARAZZOdbt Cloud Trigger Run and Poll to Completion
Trigger a dbt Cloud job run, poll the run until it succeeds, then list its artifacts.
ARAZZOScroll within the panel for all 13 ·
GraphQL 1
Where a provider ships GraphQL, the schema is the contract. We profile it alongside the REST surface so the whole interface is legible in one place.
GraphQL schemas published by this provider.
dbt GraphQL API
Every time dbt Cloud runs a project, it generates and stores information about the project. The Discovery API exposes that metadata including details about models, sources, expo...
GRAPHQLPricing 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.
Dbt Plans Pricing
PLANSRate 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.
Dbt 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.
Dbt 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.
Dbt 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.
dbt API Rules
SPECTRALdbt API Rules
SPECTRALJSON Schema 2
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.
dbt Cloud Job
JSON SCHEMAdbt Cloud Run
JSON SCHEMASecurity 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.
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 dbt — 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 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 15
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 15 ·
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Commercial 3
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
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