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 4 APIs on the APIs.io network, including Health API, Inference Protocol API, Models API, and 1 more. Tagged areas include Inference, Kubernetes, Machine Learning, MLOps, and Model Serving.

KServe’s developer surface includes authentication, documentation, getting-started guide, engineering blog, and 5 more developer resources.

🌐 Visit website 📡 Source on GitHub

26.7/100 thin ▬ flat Agent 20/100 agent aware Full breakdown ↓
scored 2026-10-04 · rubric v0.23.0

AccessFreemiumSelf serve⚡ Free to try

1 published contract

Inference Kubernetes Machine Learning MLOps Model Serving

What this lets a business do 1

Business capabilities this provider's published APIs can perform, derived from its own contracts. Browse all capabilities →

Information & Data Management

BC-610

Models

POST /v1/models/{model_name}:predict POST /v1/models/{model_name}:explain POST /v2/models/{model_name}/infer

Kin Score

Kin Score How this is scored →
scored 2026-10-04 · rubric v0.23.0

Composite quality — 26.7/100 · thin

Contract Quality 7.6 / 19

Developer Ergonomics 6.4 / 15

Access Clarity 2.4 / 15

Operational Transparency 1.0 / 10

Contract Governance 0.0 / 9

Discoverability 4.3 / 8

Regulatory Posture 0.8 / 15

Create-or-Update Ergonomics 0.0 / 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 Well-Known Document 0 / 5

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics applies to this provider. This API accepts writes, so it carries 10 points of the composite. It is scored from the published contracts themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in front of it, and the first time that check is skipped a duplicate record is created. Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet, not penalised by it.

The six quality facets above are damped to 75 points between them, because the conditional facet above carries the other 25. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. 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. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

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 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 Health API

OPEN COLLECTION

Health KServe Inference Protocol API

OPEN COLLECTION

KServe Inference Protocol Health Models API

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.

Kserve Finops

FINOPS

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

AGENTIC

Resources

Get Started 1

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

AgenticAccess

AgenticAccess

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

Authentication

Authentication

Company 3

The organization behind the API

LinkedIn

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Source (apis.yml)

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
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  confidence: low
  source:
  - openapi
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: false
  try_now: true
  public: false
  label: Freemium · Self-serve signup
  confidence: medium
  source:
  - plans
  - authentication
  generated: '2026-09-03'
  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
- Machine-Learning
url: https://raw.githubusercontent.com/api-evangelist/kserve/refs/heads/main/apis.yml
created: '2025-01-01'
modified: '2026-09-16'
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 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: CapabilityMap
  url: capabilities/kserve-capability-edges.yml
  name: KServe Business Capability Map
- 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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