Apache Kafka
Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. It provides a REST Proxy API, Kafka Connect REST API, and AsyncAPI for event streaming.
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.
API Evangelist profiles Apache Kafka the way a machine reads it — 113 machine-readable artifacts across 12 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 — Apache Kafka scores 59.3/100 (developing), with a separate agent-readiness read of 70/100 (agent native). 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 Apache Kafka
Each block below is one kind of artifact we hold for Apache Kafka. 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 12
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.
Apache Kafka Messaging API
The core Kafka messaging protocol for producing and consuming records to/from topics using the native Kafka binary protocol, supporting exactly-once semantics, compaction, and p...
Apache Kafka ACL API
The ACL API from Apache Kafka — 1 operation(s) for acl.
Apache Kafka Broker API
The Broker API from Apache Kafka — 1 operation(s) for broker.
Apache Kafka Cluster API
The Cluster API from Apache Kafka — 3 operation(s) for cluster.
Apache Kafka Connectors API
The Connectors API from Apache Kafka — 8 operation(s) for connectors.
Apache Kafka Consumer Group API
The Consumer Group API from Apache Kafka — 2 operation(s) for consumer group.
Apache Kafka Offsets API
The Offsets API from Apache Kafka — 1 operation(s) for offsets.
Apache Kafka Partition API
The Partition API from Apache Kafka — 1 operation(s) for partition.
Apache Kafka Plugins API
The Plugins API from Apache Kafka — 2 operation(s) for plugins.
Apache Kafka Records API
The Records API from Apache Kafka — 1 operation(s) for records.
Apache Kafka Tasks API
The Tasks API from Apache Kafka — 3 operation(s) for tasks.
Apache Kafka Topic API
The Topic API from Apache Kafka — 2 operation(s) for topic.
Scroll within the panel for all 12 ·
Open Collections 2
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).
Kafka Connect REST API
OPEN COLLECTIONConfluent Kafka REST Proxy 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.
Apache Kafka Update a Connector Configuration
Read the current config, validate the replacement, apply it, restart, and confirm.
ARAZZOApache Kafka Decommission a Connector
Capture a connector's config and offsets, stop it cleanly, delete it, and verify it is gone.
ARAZZOApache Kafka Triage a Failed Connector
Find the connector, read its status, drill into the failing task, and restart what is broken.
ARAZZOApache Kafka Pause and Resume a Connector for Maintenance
Pause a connector for a maintenance window, confirm it stopped, then resume it and confirm recovery.
ARAZZOApache Kafka Reset Connector Offsets
Stop a connector, snapshot its offsets, wipe them entirely, and resume from a clean slate.
ARAZZOApache Kafka Rewind Connector Offsets
Stop a connector, capture its offsets, rewind them to a chosen position, and resume.
ARAZZOApache Kafka Validate and Deploy a Connector
Check the worker, confirm the plugin is installed, validate the config, then create the connector.
ARAZZOApache Kafka Review Consumer Group Lag
Resolve the cluster, list the consumer groups, and pull the lag summary and assignment for one group.
ARAZZOApache Kafka Grant a Principal Access to a Topic
Resolve the cluster, confirm the topic, audit existing ACLs, grant read access, and verify the grant.
ARAZZOApache Kafka Review Cluster and Topic Capacity
Walk a cluster from brokers to topics to the partition and replica layout of one topic.
ARAZZOApache Kafka Decommission a Topic
Confirm the topic, check for active consumer groups and bound ACLs, then delete it.
ARAZZOApache Kafka Provision a Topic and Produce a Record
Resolve the cluster, create a topic with explicit partitioning, read it back, and produce a first record.
ARAZZOScroll within the panel for all 12 ·
MCP Servers 1
Model Context Protocol servers expose these APIs directly to AI agents. We profile them because agent-native access is the fastest-growing way this provider's capabilities actually get used.
Model Context Protocol servers that expose these APIs to AI agents.
apache-kafka-mcp.yml
MCP SERVERPricing 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.
Apache Kafka 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.
Apache Kafka Finops
FINOPSFeatures 7
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.
High Throughput
Handle millions of messages per second with low latency at massive scale.
Exactly-Once Semantics
Guarantee exactly-once message delivery with idempotent producers and transactional APIs.
Distributed Replication
Automatic replication across brokers for fault tolerance and high availability.
Stream Processing
Real-time stream processing via Kafka Streams library and KSQL.
Connector Ecosystem
200+ pre-built Kafka Connect connectors for databases, clouds, and SaaS.
Log Compaction
Retain the latest value for each key with topic log compaction.
Consumer Groups
Horizontally scalable consumers with automatic partition rebalancing.
Scroll within the panel for all 7 ·
Event Specifications 1
Not every API is request/response. AsyncAPI describes the event-driven and streaming side — the webhooks and channels — so the asynchronous half of the interface is documented the same way the synchronous half is.
AsyncAPI definitions for this provider's event-driven and streaming APIs.
Apache Kafka Messaging API
Apache Kafka is a distributed event streaming platform capable of handling trillions of events a day. This spec describes the core messaging protocol for producing and consuming...
ASYNCAPISemantic 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 3
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.
JSON Schema 19
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.
ConfigValidationResult
JSON SCHEMAConnectorInfo
JSON SCHEMAConnectorPlugin
JSON SCHEMAConnectorStatus
JSON SCHEMACreateConnectorRequest
JSON SCHEMATaskInfo
JSON SCHEMATaskStatus
JSON SCHEMAKafka Record
JSON SCHEMAAcl
JSON SCHEMABroker
JSON SCHEMACluster
JSON SCHEMAConsumerGroup
JSON SCHEMACreateAclRequest
JSON SCHEMACreateTopicRequest
JSON SCHEMAPartition
JSON SCHEMAProduceRequest
JSON SCHEMAProduceResponse
JSON SCHEMATopic
JSON SCHEMAKafka Topic Configuration
JSON SCHEMAScroll within the panel for all 19 ·
JSON Structure 17
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.
Kafka Connect Config Validation Result Structure
JSON STRUCTUREKafka Connect Connector Info Structure
JSON STRUCTUREKafka Connect Connector Plugin Structure
JSON STRUCTUREKafka Connect Connector Status Structure
JSON STRUCTUREKafka Connect Create Connector Request Structure
JSON STRUCTUREKafka Connect Task Info Structure
JSON STRUCTUREKafka Connect Task Status Structure
JSON STRUCTUREKafka Rest Proxy Acl Structure
JSON STRUCTUREKafka Rest Proxy Broker Structure
JSON STRUCTUREKafka Rest Proxy Cluster Structure
JSON STRUCTUREKafka Rest Proxy Consumer Group Structure
JSON STRUCTUREKafka Rest Proxy Create Acl Request Structure
JSON STRUCTUREKafka Rest Proxy Create Topic Request Structure
JSON STRUCTUREKafka Rest Proxy Partition Structure
JSON STRUCTUREKafka Rest Proxy Produce Request Structure
JSON STRUCTUREKafka Rest Proxy Produce Response Structure
JSON STRUCTUREKafka Rest Proxy Topic Structure
JSON STRUCTUREScroll within the panel for all 17 ·
Examples 17
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.
Kafka Rest Proxy Acl Example
EXAMPLEScroll within the panel for all 17 ·
Security Posture 2
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.
Event-Driven Architecture
Build event-driven microservices with reliable message delivery.
Data Pipeline
Move data between systems at scale with exactly-once delivery guarantees.
Real-Time Analytics
Process and analyze event streams in real time with Kafka Streams.
Log Aggregation
Centralize application and infrastructure logs for analysis and alerting.
CDC (Change Data Capture)
Capture database changes and stream them to data warehouses and caches.
Integrations 6
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
Apache Spark
Spark Structured Streaming integration for batch and streaming analytics.
Apache Flink
Native Flink Kafka connector for low-latency stream processing.
Debezium
CDC platform using Kafka Connect to capture database change events.
Elasticsearch
Kafka Connect Elasticsearch sink for indexing event data.
Amazon S3
Kafka Connect S3 sink for archiving event streams to object storage.
Apache Hadoop
HDFS sink connector for streaming data into Hadoop data lake.
Resources
Every other property we hold for Apache Kafka — 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 4
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 20
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 20 ·
Build 4
SDKs, sample code, and the tooling you integrate with
Access & Security 3
Authentication, authorization, and security posture
Operate 1
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/apache-kafka · machine-readable index on apis.io