Amazon Kendra
Amazon Kendra is an intelligent enterprise search service powered by machine learning that enables organizations to index and search across multiple data sources, delivering highly accurate and relevant answers to natural language queries.
Reference-quality API operations across every facet — a rich contract, published governance, transparent operations, and machine-readable commercial terms.
API Evangelist profiles Amazon Kendra the way a machine reads it — 58 machine-readable artifacts across 8 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 Kendra scores 78.3/100 (exemplar), 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 Amazon Kendra
Each block below is one kind of artifact we hold for Amazon Kendra. 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 8
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 Kendra Data Sources API
Operations for managing data source connectors
Amazon Kendra Documents API
Operations for managing documents in the index
Amazon Kendra Experience API
Operations for managing search experiences
Amazon Kendra FAQs API
Operations for managing FAQ entries
Amazon Kendra Indexes API
Operations for creating and managing search indexes
Amazon Kendra Queries API
Operations for querying the search index
Amazon Kendra Query Suggestions API
Operations for query autocompletion
Amazon Kendra Thesaurus API
Operations for managing custom synonyms
Scroll within the panel for all 8 ·
Postman Collections 1
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.
Amazon Kendra API
POSTMANOpen 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 Kendra API
OPEN COLLECTIONArazzo Workflows 12
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.
Amazon Kendra Create FAQ and Query
Load an FAQ file from S3 into an index, wait until it is active, then query for FAQ-backed answers.
ARAZZOAmazon Kendra Create Search Experience
Wait for an index to be active, create a hosted search experience on it, and confirm it via the experiences list.
ARAZZOAmazon Kendra Create Thesaurus and Query
Load a custom synonym thesaurus from S3 into an index, wait until it is active, then run a synonym-aware query.
ARAZZOAmazon Kendra Ingest Documents and Query
Directly upload documents into an index, wait until they finish indexing, then run a search query.
ARAZZOAmazon Kendra Provision Index and Start First Sync
Create an index, wait until it is active, attach a data source, and kick off the first sync job.
ARAZZOAmazon Kendra Query Suggestions then Search
Generate type-ahead query suggestions for a partial query, then run a full search using the top suggestion.
ARAZZOAmazon Kendra Refresh Documents
Remove stale documents from an index, upload their refreshed versions, and wait until the new versions are indexed.
ARAZZOAmazon Kendra Reschedule and Resync Data Source
Update a data source's sync schedule, trigger an immediate sync, and wait for that sync to succeed.
ARAZZOAmazon Kendra Resolve Index by Name and Query
Look up an index by name, confirm it is active, and run a search query against it.
ARAZZOAmazon Kendra Retrieve Passages for RAG
Retrieve semantically relevant passages for a question and run a parallel ranked query to enrich a RAG context.
ARAZZOAmazon Kendra Sync Data Source and Query
Start a data source sync job on an existing connector, wait for it to succeed, then query the refreshed index.
ARAZZOAmazon Kendra Teardown Data Source and Index
Delete a data source connector, confirm it is gone, then delete the index that owned it.
ARAZZOScroll within the panel for all 12 ·
Pricing 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 Kendra 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 Kendra Finops
FINOPSFeatures 8
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Intelligent Search
ML-powered semantic search that understands natural language queries and context to return highly accurate answers from enterprise content.
GenAI RAG Support
Kendra Retriever API enables retrieval-augmented generation workflows with optimized passage chunking and ACL-based filtering for LLM integration.
Data Source Connectors
Native connectors for Amazon S3, SharePoint, Salesforce, ServiceNow, Google Drive, Confluence, and many more data repositories.
Relevance Tuning
Fine-tune search results based on document freshness, authoritative sources, and custom synonyms without ML expertise.
Experience Builder
No-code visual interface to build, customize, and launch search applications with drag-and-drop components.
Search Analytics Dashboard
Visibility into quality and usability metrics and user interaction patterns to identify content gaps.
Custom Document Enrichment
Preprocessing capabilities for metadata enrichment, document classification, entity extraction, and AWS AI service integration.
Incremental Learning
Learns from user interactions and feedback to promote preferred documents to the top of search results over time.
Scroll within the panel for all 8 ·
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.
Amazon Kendra 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.
Amazon Kendra API Rules
SPECTRALAmazon Kendra API Rules
SPECTRALJSON Schema 4
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.
JSON Structure 4
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 Kendra Data Source Structure
JSON STRUCTUREAmazon Kendra Faq Structure
JSON STRUCTUREAmazon Kendra Index Structure
JSON STRUCTUREAmazon Kendra Query Result Structure
JSON STRUCTUREExamples 4
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.
Amazon Kendra Faq Example
EXAMPLEAmazon Kendra Index Example
EXAMPLESecurity 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.
Use Cases 5
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Employee Productivity
Help employees find accurate answers and data-driven insights across internal knowledge bases and document repositories.
Customer Service
Power self-service chatbots and agent-assist solutions for contact centers with intelligent search.
SaaS Application Integration
Integrate intelligent search and conversational AI into customer-facing applications via the Kendra API.
Generative AI Applications
Use Kendra GenAI indices in Amazon Q Business and Amazon Bedrock knowledge bases to build RAG applications.
Enterprise Knowledge Management
Index and search across multiple heterogeneous data sources to create a unified knowledge search experience.
Resources
Every other property we hold for Amazon Kendra — 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 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 14
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 14 ·
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 5
Authentication, authorization, and security posture
Operate 3
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
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