TensorFlow

TensorFlow is an end-to-end open source machine learning platform developed by Google. It provides a comprehensive ecosystem of tools, libraries, and community resources for building and deploying ML-powered applications, including model training, serving, mobile/edge deployment, and a hub of pre-trained models. TensorFlow Serving exposes REST and gRPC APIs for production model inference.

TensorFlow publishes 7 API contracts indexed on the APIs.io network, including Inference API, Models API, and 5 more. Tagged areas include Artificial Intelligence, Deep Learning, JavaScript, Machine Learning, and Model Serving.

The TensorFlow catalog on APIs.io includes 1 JSON-LD context and 2 Spectral governance rulesets.

TensorFlow’s developer surface includes authentication, sandbox, changelog, CLI, engineering blog, YouTube channel, Stack Overflow tag, and 32 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

35.1/100 thin ▬ flat Agent 27/100 agent aware Front door AI 6/6 dominant Heartbeat 50/100 alive self hosted · Apache-2.0 Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreeOpen⚡ Free to try

1 published contract

Artificial Intelligence Deep Learning JavaScript Machine Learning Model Serving Neural Networks Open Source Python

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

InferenceModels

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 35.1/100 · thin

Contract Quality 9.9 / 19

Developer Ergonomics 6.4 / 15

Access Clarity 0.8 / 15

Operational Transparency 2.6 / 10

Contract Governance 2.9 / 9

Discoverability 4.3 / 8

Regulatory Posture 2.3 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 27/100 · 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 8 / 8

Request/Response Examples 7 / 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

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

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/.

Show this score on your site.

It updates itself when the score changes. Paste this where you link to your API docs:

<a href="https://apis.io/providers/tensorflow/"><img src="https://apis.io/badge/tensorflow/card.svg" alt="TensorFlow on APIs.io — Kin Score by API Evangelist"></a>

Other styles, a README pill and a shields.io endpoint are on the badge page.

Raise your score.

Agent readiness — checks not met, largest first (exact, from this profile):

MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document
Delegated User Identity +6 pts — a served discovery document listing authorization_code in grant_types_supported (served), else an oauth2 authorizationCode flow or openIdConnect declared in an OpenAPI (documented)
Typed Event Surface +6 pts — AsyncAPI document, OR webhooks/callbacks objects in the as-published OpenAPI, OR common[].type includes Webhooks

7 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Access Clarity scores 5.3 — up to +18.9 composite points
Contract Quality scores 52.6 — up to +11.9 composite points
Developer Ergonomics scores 42.9 — up to +11.4 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

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 the provider profile at artifacts.apis.io/tensorflow/apis.yml: open an issue on github.com/api-evangelist/tensorflow to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
MLOps and AI/ML Infrastructure (LF AI & Data, MLPerf, Kubeflow)	standard	50.8	-	-
OpenSSF Best Practices Badge Holders	standard	50.8	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

OpenAPI

measured — observed by APIs.io (published)

APIs 7

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

TensorFlow Core API

The foundational Python and C++ API for building and training machine learning models using TensorFlow.

TensorFlow.js API

A JavaScript library for training and deploying ML models in the browser and on Node.js.

TensorFlow Lite API

Lightweight solution for ML inference on mobile and embedded devices, optimized for on-device model execution.

TensorFlow Hub API

A library and repository of reusable pre-trained machine learning modules, enabling transfer learning across text, image, video, and audio domains.

TensorBoard API

TensorFlow's visualization toolkit for experiment tracking, model debugging, and performance profiling via an embedded web server with REST endpoints.

TensorFlow Inference API

Model inference operations including classify, regress, and predict

TensorFlow Models API

Model status and metadata operations

Scroll for all 7

Open Collections 3

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

TensorFlow Serving REST Inference API

OPEN COLLECTION

TensorFlow Serving REST Inference Models API

OPEN COLLECTION

TensorFlow Serving REST API

OPEN COLLECTION

Arazzo Workflows 7

Multi-step API workflows described with the Arazzo specification.

TensorFlow Serving Preflight and Classify

Confirm a model is loaded and its signature is known before running classification inference.

ARAZZO

TensorFlow Serving Route Inference by Version Label

Resolve a version label such as stable or canary to a concrete version, then run inference pinned to it.

ARAZZO

TensorFlow Serving Pinned Reproducible Example Scoring

Pin a model version and score the same tf.Example inputs through both its classify and regress signatures.

ARAZZO

TensorFlow Serving Preflight and Predict

Confirm a model is loaded and its signature is known before running prediction inference.

ARAZZO

TensorFlow Serving Preflight and Regress

Confirm a model is loaded and its signature is known before running regression inference.

ARAZZO

TensorFlow Serving Gate a Rollout on Version Readiness

Poll a newly exported model version until it reports AVAILABLE, then smoke test it before traffic is shifted.

ARAZZO

TensorFlow Serving Compare a Candidate Version Against the Default

Score the same instances against a pinned candidate version and the default version to measure rollout drift.

ARAZZO

Scroll for all 7

TensorFlow API pricing

Not yet checked against TensorFlow's own pricing page. Compiled by API Evangelist on 2026-05-05 from www.tensorflow.org/; confirm before you rely on a figure. A free plan or tier is listed.

Plan	Price
Open Source freemium	Free

Plan details, limits and sources →

Rate limits

Self-Hosted Inference: bounded by self-hosted hardware / serving stack varies

Compiled by API Evangelist, not yet checked against TensorFlow's documentation. Rate-limit details →

Pricing Plans 1

Published pricing tiers and plan structures.

Tensorflow Plans Pricing

1 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Tensorflow Rate Limits

1 limits

RATE LIMITS

Service Levels 1

Uptime the provider promises or reports, as SLA4OAI. Read from its own pages; APIs.io runs no monitors.

TensorFlow

SLA

FinOps 1

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

Tensorflow Finops

FINOPS

Semantic Vocabularies 1

JSON-LD contexts and semantic vocabularies used across these APIs.

Tensorflow Context

4 classes · 15 properties

JSON-LD

Spectral Rules 2

Spectral governance rulesets for linting and validating these APIs.

TensorFlow — jsonschema rules

5 rules · 4 warnings 1 info

SPECTRAL

TensorFlow — serving rules

13 rules · 5 errors 7 warnings

SPECTRAL

OpenAPI Overlays 1

Overlays applied on top of this provider's contracts. Each card says who wrote it: a document the provider publishes, or one API Evangelist derived or generated.

Tensorflow Serving Overlay

4 actions · update · tensorflow-serving-openapi.yml

DERIVED

JSON Schema 3

Standalone JSON Schema definitions for this provider's data models.

TensorFlow Serving Model Status Response

1 properties

JSON SCHEMA

TensorFlow Serving Prediction Request

3 properties

JSON SCHEMA

TensorFlow Serving Prediction Response

3 properties

JSON SCHEMA

JSON Structure 1

JSON Structure definitions describing this provider's data shapes.

Tensorflow Serving Prediction Request Structure

0 properties

JSON STRUCTURE

Examples 2

Example request and response payloads for these APIs.

Tensorflow Serving Model Status Example

4 fields

EXAMPLE

Tensorflow Serving Predict Example

4 fields

EXAMPLE

Security Posture 2

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

Tensorflow Authentication

0 schemes

SECURITY

Tensorflow Domain Security

TLSv1.3 · HSTS

SECURITY

Agentic Access 1

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

Tensorflow Agentic Access

11 operations · 6 acting

AGENTIC

Resources

Get Started 1

Portal, sign-up, and the first successful call

Sandbox

Sandbox

Documentation 1

Reference material describing how the API behaves

OpenAPI

OpenAPI

Agent Surfaces 3

MCP servers, agent skills, and machine-readable catalogs

AgenticAccess

AgenticAccess

X-MCPServerCandidate

X-MCPServerCandidate

LLMsTxt

LLMsTxt

Design & Contract 13

Pagination, idempotency, versioning, errors, and events

Conformance

ErrorCatalog

Lifecycle

Conventions

DataModel

Arazzo

Arazzo

Arazzo

Arazzo

Arazzo

Arazzo

Arazzo

Vocabulary

Scroll for all 13

Build 3

SDKs, sample code, and the tooling you integrate with

Packages

Packages

CLI

CLI

GitHubOrg

GitHubOrg

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Learn 1

Tutorials, courses, talks, and written guidance

YouTube

YouTube

Operate 4

Status, limits, changes, and where to get help

RateLimits

ChangeLog

Forums

StackOverflow

Commercial 3

Pricing, plans, and the legal terms of use

Plans

Plans

FinOps

FinOps

License

License

Company 4

The organization behind the API

Website

Website

LinkedIn

Blog

Blog

Twitter

Twitter

Other 4

Properties that don't map to a standard resource type

CapabilityMap

Overlay

Protobuf

Protobuf

Source (apis.yml)

aid: tensorflow
name: TensorFlow
description: TensorFlow is an end-to-end open source machine learning platform developed by Google. It provides a comprehensive
  ecosystem of tools, libraries, and community resources for building and deploying ML-powered applications, including model
  training, serving, mobile/edge deployment, and a hub of pre-trained models. TensorFlow Serving exposes REST and gRPC APIs
  for production model inference.
type: Index
deliveryModel:
  model: self-hosted
  license: Apache-2.0
  license_evidence:
    repo: tensorflow/tensorflow
    spdx: Apache-2.0
    stars: 200306
  open_source: true
  commercial: false
  callable_host: false
  label: Self-hosted open source · you run it yourself
  confidence: medium
  source:
  - openapi
  - repository-license
  generated: '2026-09-25'
  method: derived
accessModel:
  pricing: free
  onboarding: open
  trial: false
  try_now: true
  public: true
  gated: none
  gated_source:
  - onboarding
  label: Free · Open access
  confidence: high
  source:
  - plans
  - authentication
  - security
  - sandbox
  generated: '2026-11-06'
  method: derived
image: https://www.tensorflow.org/images/tf_logo_social.png
tags:
- Artificial Intelligence
- Deep Learning
- JavaScript
- Machine Learning
- Model Serving
- Neural Networks
- Open Source
- Python
tags_raw:
- AI
- Deep Learning
- JavaScript
- Machine Learning
- Model Serving
- Neural Networks
- Open Source
- Python
- Machine-Learning
- Open-Source
url: https://raw.githubusercontent.com/api-evangelist/tensorflow/refs/heads/main/apis.yml
created: '2024-01-15'
modified: '2026-09-16'
specificationVersion: '0.23'
apis:
- aid: tensorflow:tensorflow-core
  name: TensorFlow Core API
  description: The foundational Python and C++ API for building and training machine learning models using TensorFlow.
  humanURL: https://www.tensorflow.org/api_docs/python/tf
  baseURL: https://www.tensorflow.org/api_docs
  tags:
  - Core API
  - Machine Learning
  - Python
  tags_raw:
  - Core API
  - Machine Learning
  - Python
  - Machine-Learning
  properties:
  - type: Documentation
    url: https://www.tensorflow.org/api_docs/python/tf
  - type: Tutorial
    url: https://www.tensorflow.org/tutorials
  - type: GitHub
    url: https://github.com/tensorflow/tensorflow
  - type: Guide
    url: https://www.tensorflow.org/guide
- aid: tensorflow:tensorflow-js
  name: TensorFlow.js API
  description: A JavaScript library for training and deploying ML models in the browser and on Node.js.
  humanURL: https://js.tensorflow.org/
  baseURL: https://cdn.jsdelivr.net/npm/@tensorflow/tfjs
  tags:
  - Browser
  - JavaScript
  - Node.js
  properties:
  - type: Documentation
    url: https://js.tensorflow.org/api/latest/
  - type: Tutorial
    url: https://js.tensorflow.org/tutorials/
  - type: GitHub
    url: https://github.com/tensorflow/tfjs
  - type: NPM
    url: https://www.npmjs.com/package/@tensorflow/tfjs
- aid: tensorflow:tensorflow-lite
  name: TensorFlow Lite API
  description: Lightweight solution for ML inference on mobile and embedded devices, optimized for on-device model execution.
  humanURL: https://www.tensorflow.org/lite
  baseURL: https://www.tensorflow.org/lite/api_docs
  tags:
  - Edge Computing
  - Embedded
  - Mobile
  - On-Device AI
  properties:
  - type: Documentation
    url: https://www.tensorflow.org/lite/api_docs
  - type: Guide
    url: https://www.tensorflow.org/lite/guide
  - type: Examples
    url: https://www.tensorflow.org/lite/examples
  - type: GitHub
    url: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite
- aid: tensorflow:tensorflow-hub
  name: TensorFlow Hub API
  description: A library and repository of reusable pre-trained machine learning modules, enabling transfer learning across
    text, image, video, and audio domains.
  humanURL: https://tfhub.dev/
  baseURL: https://tfhub.dev/
  tags:
  - Model Repository
  - Pre-Trained Models
  - Transfer Learning
  properties:
  - type: Documentation
    url: https://www.tensorflow.org/hub/api_docs/python/hub
  - type: Models
    url: https://tfhub.dev/
  - type: GitHub
    url: https://github.com/tensorflow/hub
- aid: tensorflow:tensorboard
  name: TensorBoard API
  description: TensorFlow's visualization toolkit for experiment tracking, model debugging, and performance profiling via
    an embedded web server with REST endpoints.
  humanURL: https://www.tensorflow.org/tensorboard
  tags:
  - Model Debugging
  - Monitoring
  - Visualization
  properties:
  - type: Documentation
    url: https://www.tensorflow.org/tensorboard/get_started
  - type: GitHub
    url: https://github.com/tensorflow/tensorboard
- aid: tensorflow:tensorflow-inference-api
  name: TensorFlow Inference API
  description: Model inference operations including classify, regress, and predict
  humanURL: https://www.tensorflow.org/tfx/serving/api_rest
  baseURL: http://host:8501
  tags:
  - Inference
  properties:
  - type: OpenAPI
    url: openapi/tensorflow-inference-api-openapi.yml
  - type: Documentation
    url: https://www.tensorflow.org/tfx/serving/api_rest
  - type: GitHub
    url: https://github.com/tensorflow/serving
- aid: tensorflow:tensorflow-models-api
  name: TensorFlow Models API
  description: Model status and metadata operations
  humanURL: https://www.tensorflow.org/tfx/serving/api_rest
  baseURL: http://host:8501
  tags:
  - Models
  properties:
  - type: OpenAPI
    url: openapi/tensorflow-models-api-openapi.yml
  - type: Documentation
    url: https://www.tensorflow.org/tfx/serving/api_rest
  - type: GitHub
    url: https://github.com/tensorflow/serving
maintainers:
- FN: Google Brain Team
  email: tensorflow@googlegroups.com
  url: https://www.tensorflow.org/
include:
- name: TensorFlow Community
  url: https://www.tensorflow.org/community
common:
- type: Plans
  url: plans/tensorflow-plans-pricing.yml
- type: RateLimits
  url: rate-limits/tensorflow-rate-limits.yml
- type: FinOps
  url: finops/tensorflow-finops.yml
- type: CapabilityMap
  url: capabilities/tensorflow-capability-edges.yml
  name: TensorFlow Business Capability Map
- type: Website
  url: https://tensorflow.org
- type: AgenticAccess
  url: agentic-access/tensorflow-agentic-access.yml
- type: DomainSecurity
  url: security/tensorflow-domain-security.yml
- type: Packages
  url: packages/tensorflow-packages.yml
- type: X-MCPServerCandidate
  url: mcp/tensorflow-mcp.yml
  note: 'Renamed from MCPServer 2026-09-03 (roadmap#247): the manifest self-describes as status: candidate — a tool list derived
    from the published API contracts, not an existing server. The scorer already read the manifest and reported mcp_server
    correctly; the MCPServer type was crediting the artifact-type surfaces with a server that does not exist.'
- type: LLMsTxt
  url: llms/tensorflow-llms.txt
- type: Overlay
  url: overlays/tensorflow-serving-overlay.yaml
- type: Protobuf
  url: grpc/tensorflow-prediction-service.proto
- type: Protobuf
  url: grpc/tensorflow-model-service.proto
- type: Conformance
  url: conformance/tensorflow-conformance.yml
- type: ErrorCatalog
  url: errors/tensorflow-problem-types.yml
- type: Lifecycle
  url: lifecycle/tensorflow-lifecycle.yml
- type: Authentication
  url: authentication/tensorflow-authentication.yml
- type: Sandbox
  url: sandbox/tensorflow-sandbox.yml
- type: Conventions
  url: conventions/tensorflow-conventions.yml
- type: ChangeLog
  url: changelog/tensorflow-changelog.yml
- type: CLI
  url: cli/tensorflow-cli.yml
- type: DataModel
  url: data-model/tensorflow-data-model.yml
- type: Arazzo
  url: arazzo/tensorflow-predict-preflight-workflow.yml
  name: TensorFlow Preflight a Model and Run Prediction
- type: Arazzo
  url: arazzo/tensorflow-classify-preflight-workflow.yml
  name: TensorFlow Preflight a Model and Run Classification
- type: Arazzo
  url: arazzo/tensorflow-regress-preflight-workflow.yml
  name: TensorFlow Preflight a Model and Run Regression
- type: Arazzo
  url: arazzo/tensorflow-version-canary-compare-workflow.yml
  name: TensorFlow Compare a Candidate Version Against the Default
- type: Arazzo
  url: arazzo/tensorflow-label-routed-inference-workflow.yml
  name: TensorFlow Route Inference by Version Label
- type: Arazzo
  url: arazzo/tensorflow-pinned-example-scoring-workflow.yml
  name: TensorFlow Pinned Reproducible Example Scoring
- type: Arazzo
  url: arazzo/tensorflow-rollout-readiness-workflow.yml
  name: TensorFlow Gate a Rollout on Version Readiness
- type: LinkedIn
  url: https://www.linkedin.com/showcase/tensorflowdev
- type: Blog
  url: https://blog.tensorflow.org/
- type: GitHubOrg
  url: https://github.com/tensorflow
- type: Twitter
  url: https://twitter.com/tensorflow
- type: YouTube
  url: https://www.youtube.com/tensorflow
- type: License
  url: https://github.com/tensorflow/tensorflow/blob/master/LICENSE
- type: Forums
  url: https://discuss.tensorflow.org/
- type: StackOverflow
  url: https://stackoverflow.com/questions/tagged/tensorflow
- type: OpenAPI
  url: https://raw.githubusercontent.com/api-evangelist/tensorflow/refs/heads/main/openapi/tensorflow-serving-openapi.yml
- type: Vocabulary
  url: https://raw.githubusercontent.com/api-evangelist/tensorflow/refs/heads/main/vocabulary/tensorflow-vocabulary.yml

TensorFlow API — frequently asked questions

Does TensorFlow have an API?

Yes. APIs.io lists 7 APIs from TensorFlow, including TensorFlow Core API, TensorFlow.js API and TensorFlow Lite API, and 4 more.

Is there an OpenAPI specification for the TensorFlow API?

Yes. APIs.io indexes 2 OpenAPI specifications for TensorFlow, each linked for download from this page.

How do I authenticate with the TensorFlow API?

TensorFlow uses bearer-token authentication (0 schemes). The details are profiled on APIs.io as Tensorflow Authentication.

How much does the TensorFlow API cost?

APIs.io lists 1 pricing plan for TensorFlow, with each plan's price, limits and inclusions under Pricing on this page.

Is the TensorFlow API ready for AI agents?

TensorFlow has a Kin Score of 35.1 out of 100 (thin) and an Agent Readiness score of 26.5 (agent-aware), scored by API Evangelist on 2026-11-06.

Work with this as data

Every provider here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for providers

9 MCP tools reach this

find_providersBrowse and filter every provider in the catalog.
get_provider_artifactsEvery artifact this provider publishes, grouped by type.
get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
find_cohortsEvery scored population of providers in the catalog.

All 92 tools →

Call it yourself

curl for this page

This provider

curl "https://apis.io/api/v1/providers/tensorflow"

All providers

curl "https://apis.io/api/v1/providers?limit=25"

Every operation they expose

curl "https://apis.io/api/v1/providers/tensorflow/operations?limit=25"

How their score was established

curl "https://apis.io/api/v1/providers/tensorflow/evidence"

Calls without X-API-Key need no key. Calls with it need a paid plan — get a key.

Get an API key

Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.

GitHub Google LinkedIn

A second provider on the same verified email joins the account you already have.