Amazon Q
Amazon Q is a generative AI-powered assistant that helps with various tasks including answering questions, generating content, and taking actions based on your enterprise data and systems. It is available in multiple product variants including Amazon Q Business for enterprise knowledge, Amazon Q Developer for software development, and Amazon Q in Connect for customer service agents.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles Amazon Q the way a machine reads it — 44 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 — Amazon Q scores 67.0/100 (strong), 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.
How we profile Amazon Q
Each block below is one kind of artifact we hold for Amazon Q. 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.
Amazon Q Business QApps API
API for Amazon Q Apps, a feature within Amazon Q Business that allows web experience users to create lightweight, purpose-built AI apps to fulfill specific tasks using their ent...
Amazon Q Connect API
API for Amazon Q in Connect, a generative AI-powered customer service assistant integrated with Amazon Connect. It automatically detects customer intent during calls and chats u...
Amazon Q Developer in Chat Applications API
API for Amazon Q Developer in chat applications, which enables integration of Amazon Q Developer capabilities into messaging platforms. It provides descriptions, request paramet...
Amazon Q Applications API
The Applications API from Amazon Q — 2 operation(s) for applications.
Amazon Q Conversations API
The Conversations API from Amazon Q — 1 operation(s) for conversations.
Amazon Q Data Sources API
The Data Sources API from Amazon Q — 1 operation(s) for data sources.
Amazon Q Indices API
The Indices API from Amazon Q — 1 operation(s) for indices.
Scroll within the panel for all 7 ·
Open Collections 1
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).
Amazon Q Business 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.
Amazon Q 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.
Amazon Q Finops
FINOPSSemantic Vocabularies 5
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.
Spectral 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.
Amazon Q API Rules
SPECTRALAmazon Q API Rules
SPECTRALJSON Schema 10
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.
Application
JSON SCHEMAConversation
JSON SCHEMADataSource
JSON SCHEMAIndex
JSON SCHEMAMessage
JSON SCHEMAApplication
JSON SCHEMAConversation
JSON SCHEMADataSource
JSON SCHEMAIndex
JSON SCHEMAMessage
JSON SCHEMAScroll within the panel for all 10 ·
JSON Structure 6
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.
Amazon Q Openapi Application Structure
JSON STRUCTUREAmazon Q Openapi Conversation Structure
JSON STRUCTUREAmazon Q Openapi Data Source Structure
JSON STRUCTUREAmazon Q Openapi Index Structure
JSON STRUCTUREAmazon Q Openapi Message Structure
JSON STRUCTUREAmazon Q Structure
JSON STRUCTUREExamples 5
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.
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 Amazon Q — 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 4
Portal, sign-up, and the first successful call
Documentation 7
Reference material describing how the API behaves
Scroll within the panel for all 7 ·
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 12
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 12 ·
Build 7
SDKs, sample code, and the tooling you integrate with
Scroll within the panel for all 7 ·
Access & Security 4
Authentication, authorization, and security posture
Operate 4
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 1
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/amazon-q · machine-readable index on apis.io