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Amazon Braket website screenshot

Amazon Braket

Amazon Braket is a fully managed quantum computing service that helps researchers and developers explore and build quantum algorithms, test them on quantum circuit simulators, and run them on different quantum hardware technologies. Braket provides access to multiple quantum processors from IonQ, Rigetti, QuEra, Oxford Quantum Circuits, and IQM, as well as high-performance quantum circuit simulators. It supports hybrid quantum-classical algorithms through Braket Hybrid Jobs.

agent ready

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.

Kin Score

API Evangelist profiles Amazon Braket the way a machine reads it — 17 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 — Amazon Braket scores 56.3/100 (developing), with a separate agent-readiness read of 55/100 (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 Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 56.3/100 · developing
Contract Quality 18.0 / 25
Developer Ergonomics 10.9 / 20
Commercial Clarity 7.9 / 20
Operational Transparency 0.7 / 13
Governance 8.8 / 12
Discoverability 10.0 / 10
Agent readiness — 55/100 · agent ready
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
MCP Server 0 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 7 / 7
Rate-Limit Signaling 0 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 4 / 4
Consent & Bot Identity 3 / 3

How we profile Amazon Braket

Each block below is one kind of artifact we hold for Amazon Braket. 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.

Amazon Braket Devices API

Discover and retrieve details about quantum devices

Amazon Braket Jobs API

Manage hybrid quantum-classical jobs

Amazon Braket Quantum Tasks API

Submit and manage quantum tasks on QPUs and simulators

Amazon Braket Spending Limits API

Control QPU and simulator spending

Amazon Braket Tags API

Manage resource tags

Semantic 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.

context Context

23 classes · 3 properties

JSON-LD

Spectral Rules 1

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.

Amazon Braket API Rules

5 rules · 3 warnings

SPECTRAL

JSON Schema 1

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.

Quantum Task

10 properties

JSON SCHEMA

JSON Structure 1

JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.

JSON Structure definitions describing this provider's data shapes.

Braket Resource Structure

0 properties

JSON STRUCTURE

Examples 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 4

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.

Amazon Braket Authentication

apiKey · 1 scheme

SECURITY

Amazon Braket Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Amazon Braket Vulnerability Disclosure

security.txt · contact published

SECURITY

Amazon Braket Trust Center

PCI DSS, HIPAA, FedRAMP, GDPR, FIPS 140

SECURITY

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.

Amazon Braket Agentic Access

17 operations · 13 acting

17 operations · 13 acting

AGENTIC

Resources

Every other property we hold for Amazon Braket — 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 3

Portal, sign-up, and the first successful call

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

Build 4

SDKs, sample code, and the tooling you integrate with

Operate 2

Status, limits, changes, and where to get help

Commercial 3

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

← All providers · Data indexed from github.com/api-evangelist/amazon-braket · machine-readable index on apis.io