KServe website screenshot

KServe

KServe is a standard model inference platform on Kubernetes, built for highly scalable use cases. It provides performant, standardized inference protocol across ML frameworks including TensorFlow, PyTorch, scikit-learn, XGBoost, and more.

KServe publishes 3 APIs on the APIs.io network: Health API, KServe Inference Protocol API, and Models API. Tagged areas include Inference, Kubernetes, Machine-Learning, MLOps, and Model Serving.

KServe’s developer surface includes authentication, documentation, getting-started guide, engineering blog, and 4 more developer resources.

29.4/100 thin ▬ flat Agent 20/100 agent aware Full breakdown ↓
scored 2026-08-25 · rubric v0.14.0
AccessFreemiumSelf serve⚡ Free to try
4 APIs
InferenceKubernetesMachine-LearningMLOpsModel Serving

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-08-25 · rubric v0.14.0
Composite quality — 29.4/100 · thin
Contract Quality 11.2 / 25
Developer Ergonomics 7.1 / 20
Access Clarity 3.2 / 20
Operational Transparency 1.4 / 13
Contract Governance 0.0 / 12
Discoverability 6.5 / 10
Agent readiness — 20/100 · agent aware
Machine-Readable Contract 18 / 18
Agentic Access Contract 10 / 10
Documented Reversibility 0 / 6
MCP Server 0 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 7 / 7
Typed Event Surface 0 / 6
Agent Skills 0 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3
A2A Agent Card 0 / 8
Dry-Run / Simulate Mode 0 / 4
Delegated User Identity 0 / 6
Protected Resource Metadata 0 / 5
Registration Without a Human 0 / 6
Agentic Commerce Surface 0 / 5
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/kserve: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 4

Individual APIs this provider publishes, each with its own machine-readable definition.

KServe Inference API

KServe's standardized model inference protocol for serving predictions across multiple ML frameworks on Kubernetes.

KServe Health API

The Health API from KServe — 2 operation(s) for health.

KServe KServe Inference Protocol API

The KServe Inference Protocol API from KServe — 1 operation(s) for kserve inference protocol.

KServe Models API

The Models API from KServe — 7 operation(s) for models.

Open Collections 5

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

API Collection

OPEN COLLECTION

KServe Inference Protocol

OPEN COLLECTION

Pricing Plans 1

Published pricing tiers and plan structures.

Kserve Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Kserve Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Kserve Authentication

http · 1 scheme

SECURITY

Agentic Access 1

Recommended x-agentic-access execution contracts for AI agents.

Kserve Agentic Access

10 operations · 3 acting

10 operations · 3 acting

AGENTIC

Resources

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

Build 1

SDKs, sample code, and the tooling you integrate with

Access & Security 1

Authentication, authorization, and security posture

Company 3

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: kserve
name: KServe
description: KServe is a standard model inference platform on Kubernetes, built for highly scalable use cases. It provides
  performant, standardized inference protocol across ML frameworks including TensorFlow, PyTorch, scikit-learn, XGBoost, and
  more.
type: Index
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: false
  try_now: true
  public: false
  label: Freemium · Self-serve signup
  confidence: high
  source:
  - plans
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/kserve.png
tags:
- Inference
- Kubernetes
- Machine-Learning
- MLOps
- Model Serving
tags_raw:
- Inference
- Kubernetes
- Machine Learning
- MLOps
- Model Serving
url: https://raw.githubusercontent.com/api-evangelist/kserve/refs/heads/main/apis.yml
created: '2025-01-01'
modified: '2026-04-28'
specificationVersion: '0.23'
apis:
- aid: kserve:inference-api
  name: KServe Inference API
  description: KServe's standardized model inference protocol for serving predictions across multiple ML frameworks on Kubernetes.
  humanURL: https://kserve.github.io/website/
  tags:
  - Inference
  - Model Serving
  properties:
  - type: Documentation
    url: https://kserve.github.io/website/latest/get_started/
  - type: Reference
    url: https://kserve.github.io/website/latest/reference/api/
- aid: kserve:kserve-health-api
  name: KServe Health API
  description: The Health API from KServe — 2 operation(s) for health.
  humanURL: https://kserve.github.io/website/
  tags:
  - Health
  properties:
  - type: OpenAPI
    url: openapi/kserve-health-api-openapi.yml
- aid: kserve:kserve-kserve-inference-protocol-api
  name: KServe KServe Inference Protocol API
  description: The KServe Inference Protocol API from KServe — 1 operation(s) for kserve inference protocol.
  humanURL: https://kserve.github.io/website/
  tags:
  - KServe Inference Protocol
  properties:
  - type: OpenAPI
    url: openapi/kserve-kserve-inference-protocol-api-openapi.yml
- aid: kserve:kserve-models-api
  name: KServe Models API
  description: The Models API from KServe — 7 operation(s) for models.
  humanURL: https://kserve.github.io/website/
  tags:
  - Models
  properties:
  - type: OpenAPI
    url: openapi/kserve-models-api-openapi.yml
common:
- type: AgenticAccess
  url: agentic-access/kserve-agentic-access.yml
- type: Authentication
  url: authentication/kserve-authentication.yml
- type: LinkedIn
  url: https://www.linkedin.com/company/kserve-project
- type: Website
  url: https://kserve.github.io/website/
- type: Documentation
  url: https://kserve.github.io/website/latest/
- type: GettingStarted
  url: https://kserve.github.io/website/latest/get_started/
- type: GitHubOrganization
  url: https://github.com/kserve/kserve
- url: https://kserve.github.io/website/blog/atom.xml
  type: Blog
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

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