# TensorFlow

**Canonical:** https://apis.io/providers/tensorflow/  
**APIs profiled:** 7

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.

## Kin Score — 38.8 / 100 (thin)

Scored 2026-08-20 under rubric 0.12.0. Trend: flat (+0.0 from 38.8).

| Facet | Score |
|---|---|
| Discoverability | 72.2 |
| Contract Quality | 55.6 |
| Governance | 41.7 |
| Contract Governance | 41.7 |
| Operational Transparency | 26.3 |
| Developer Ergonomics | 33.3 |
| Commercial Clarity | 13.2 |
| Access Clarity | 13.2 |

## Agent readiness — 35.9 (agent-ready)

| Dimension | Value |
|---|---|
| Spec Presence | yes |
| Agentic Access | derived |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | yes |
| Idempotency | no |
| Error Semantics | verified |
| OpenAPI Examples | no |
| Rate Limit Signal | documented |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Free · Open access — onboarding: open, pricing: free, trial: no (confidence: high).

## APIs (7)

- **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

## MCP servers (1)

- **TensorFlow MCP Server**

## Agentic access (1)

- **Tensorflow Agentic Access** — 11 operations · 6 acting

## Security (2)

- **Tensorflow Authentication** — 0 schemes
- **Tensorflow Domain Security** — TLSv1.3 · HSTS

## Plans (1)

- **Tensorflow Plans Pricing**

## Tags

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

---

Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/tensorflow/). Scores are computed from the provider's own public artifacts under a published rubric.