Ray

Ray is an open-source unified compute framework, stewarded by Anyscale, that scales Python and AI workloads from a laptop to a cluster. It consists of Ray Core (a distributed runtime) and a set of AI libraries (Ray Train, Ray Data, Ray Tune, Ray Serve, RLlib) for training, batch inference, hyperparameter search, and model serving. Ray clusters expose a Dashboard and Jobs REST API on the head node (default port 8265) for submitting jobs, inspecting actors and tasks, and serving deployed applications via Ray Serve HTTP endpoints.

Ray publishes 2 APIs on the APIs.io network: Jobs API and Version API. Tagged areas include Distributed Computing, Machine-Learning, AI Infrastructure, Python, and Model Serving.

Ray’s developer surface includes documentation, engineering blog, and 10 more developer resources.

🌐 Visit website 📡 Source on GitHub

21.6/100 emerging ▬ flat Agent 15/100 agent aware Full breakdown ↓
scored 2026-08-25 · rubric v0.14.0

5 APIs

Distributed Computing Machine-Learning AI Infrastructure Python Model Serving Open-Source Compute

Kin Score

Kin Score How this is scored →
scored 2026-08-25 · rubric v0.14.0

Composite quality — 21.6/100 · emerging

Contract Quality 10.6 / 25

Developer Ergonomics 3.3 / 20

Access Clarity 0.0 / 20

Operational Transparency 0.3 / 13

Contract Governance 0.0 / 12

Discoverability 7.4 / 10

Agent readiness — 15/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 0 / 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/ray: 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 5

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

AGENTIC

Resources

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 2

SDKs, sample code, and the tooling you integrate with

GitHubRepository

GitHubRepository

GitHubOrganization

GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

Slack

Slack

Forums

Forums

Issues

Issues

Commercial 1

Pricing, plans, and the legal terms of use

License

License

Company 2

The organization behind the API

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

Anyscale

Anyscale

Source (apis.yml)

aid: ray
name: Ray
description: Ray is an open-source unified compute framework, stewarded by Anyscale, that scales Python and AI workloads from
  a laptop to a cluster. It consists of Ray Core (a distributed runtime) and a set of AI libraries (Ray Train, Ray Data, Ray
  Tune, Ray Serve, RLlib) for training, batch inference, hyperparameter search, and model serving. Ray clusters expose a Dashboard
  and Jobs REST API on the head node (default port 8265) for submitting jobs, inspecting actors and tasks, and serving deployed
  applications via Ray Serve HTTP endpoints.
type: Index
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/ray.png
tags:
- Distributed Computing
- Machine-Learning
- AI Infrastructure
- Python
- Model Serving
- Open-Source
- Compute
tags_raw:
- Distributed Computing
- Machine Learning
- AI Infrastructure
- Python
- Model Serving
- Open Source
- Compute
url: https://raw.githubusercontent.com/api-evangelist/ray/refs/heads/main/apis.yml
created: '2026-05-11'
modified: '2026-05-11'
specificationVersion: '0.23'
apis:
- aid: ray:jobs-api
  name: Ray Jobs REST API
  description: REST API on the Ray head node for submitting, listing, inspecting, and stopping Ray jobs, plus streaming logs.
    Default base URL is http://<head-node>:8265/api/jobs/. Open-source clusters are typically unauthenticated; production
    deployments rely on network controls or Anyscale-managed authentication.
  humanURL: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/rest.html
  baseURL: http://127.0.0.1:8265/api
  tags:
  - Job
  - Cluster
  - Submission
  - Logs
  tags_raw:
  - Jobs
  - Cluster
  - Submission
  - Logs
  properties:
  - type: Documentation
    url: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/rest.html
  - type: Python SDK
    url: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/sdk.html
  - type: CLI
    url: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/cli.html
- aid: ray:dashboard-api
  name: Ray Dashboard API
  description: Internal REST API powering the Ray Dashboard, exposing endpoints for nodes, actors, tasks, placement groups,
    runtime environments, and cluster events. Same base URL as the Jobs API (http://<head>:8265).
  humanURL: https://docs.ray.io/en/latest/ray-observability/getting-started.html
  baseURL: http://127.0.0.1:8265/api
  tags:
  - Observability
  - Dashboard
  - Cluster State
  - Actors
  properties:
  - type: Documentation
    url: https://docs.ray.io/en/latest/ray-observability/getting-started.html
- aid: ray:serve-api
  name: Ray Serve HTTP API
  description: HTTP interface for invoking models and applications deployed via Ray Serve. Each deployed application is exposed
    as an HTTP endpoint on the Serve HTTP proxy (default port 8000); authentication and routing are configured per deployment.
  humanURL: https://docs.ray.io/en/latest/serve/index.html
  baseURL: http://127.0.0.1:8000
  tags:
  - Model Serving
  - Inference
  - HTTP
  properties:
  - type: Documentation
    url: https://docs.ray.io/en/latest/serve/index.html
  - type: Production Guide
    url: https://docs.ray.io/en/latest/serve/production-guide/index.html
- aid: ray:ray-jobs-api
  name: Ray Jobs API
  description: The Jobs API from Ray — 4 operation(s) for jobs.
  humanURL: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/rest.html
  baseURL: http://127.0.0.1:8265/api
  tags:
  - Job
  tags_raw:
  - Jobs
  properties:
  - type: OpenAPI
    url: openapi/ray-jobs-api-openapi.yml
- aid: ray:ray-version-api
  name: Ray Version API
  description: The Version API from Ray — 1 operation(s) for version.
  humanURL: https://docs.ray.io/en/latest/cluster/running-applications/job-submission/rest.html
  baseURL: http://127.0.0.1:8265/api
  tags:
  - Version
  properties:
  - type: OpenAPI
    url: openapi/ray-version-api-openapi.yml
common:
- type: AgenticAccess
  url: agentic-access/ray-agentic-access.yml
- type: DomainSecurity
  url: security/ray-domain-security.yml
- type: Website
  url: https://www.ray.io
- type: Documentation
  url: https://docs.ray.io
- type: GitHubRepository
  url: https://github.com/ray-project/ray
- type: GitHubOrganization
  url: https://github.com/ray-project
- type: Anyscale
  url: https://www.anyscale.com
- type: Slack
  url: https://www.ray.io/community
- type: Forums
  url: https://discuss.ray.io
- type: Blog
  url: https://www.anyscale.com/blog
- type: Issues
  url: https://github.com/ray-project/ray/issues
- type: License
  url: https://github.com/ray-project/ray/blob/master/LICENSE
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

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Ray

Kin Score

APIs 5

Ray Jobs REST API

Ray Dashboard API

Ray Serve HTTP API

Ray Jobs API

Ray Version API

Open Collections 4

API Collection

Ray REST Jobs API

Ray REST Jobs Version API