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Google Gemini website screenshot

Google Gemini

Google's multimodal AI model APIs for text, image, audio, and video understanding.

agent ready

Real signal across most facets with visible, nameable gaps — the contract exists but is thin, or the portal is good while governance and commercial terms are absent.

Kin Score

API Evangelist profiles Google Gemini the way a machine reads it — 56 machine-readable artifacts across 15 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.

Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Google Gemini scores 58.9/100 (developing), with a separate agent-readiness read of 59/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.

Kin Score

This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 58.9/100 · developing
Contract Quality 21.7 / 25
Developer Ergonomics 3.5 / 20
Commercial Clarity 12.1 / 20
Operational Transparency 6.8 / 13
Governance 7.3 / 12
Discoverability 7.5 / 10
Agent readiness — 59/100 · agent ready
Machine-Readable Contract 18 / 18
Agentic Access Contract 15 / 15
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 6 / 6
Agent Skills 5 / 5
Well-Known Catalog 0 / 4
Consent & Bot Identity 0 / 3

How we profile Google Gemini

Each block below is one kind of artifact we hold for Google Gemini. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.

APIs 15

Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.

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

Gemini Pro API

Advanced reasoning and complex task handling.

Gemini Pro Vision API

Multimodal understanding of text and images.

Gemini Ultra API

Most capable model for highly complex tasks.

Gemini Embedding API

Generate text embedding vectors for semantic search, classification, clustering, and retrieval tasks using the gemini-embedding-001 model.

Gemini Live API

Low-latency real-time voice and video interactions with Gemini using WebSockets for streaming multimodal input and output.

Gemini Context Caching API

Cache input tokens for repeated use across multiple requests to reduce costs and improve latency for large context workloads.

Gemini Fine-Tuning API

Customize Gemini model behavior for specific tasks using supervised fine-tuning with your own training data.

Gemini Interactions API

Unified interface for interacting with Gemini models and agents providing a consistent way to manage multi-turn conversations and tool use.

Vertex AI Gemini API

Enterprise-grade access to Gemini models through Google Cloud Vertex AI with advanced features including grounding, safety filters, and regional endpoints.

Vertex AI Imagen API

Generate and edit images using Google Imagen models on Vertex AI for high-quality image creation from text prompts.

Vertex AI Gemini Live API

Enterprise real-time multimodal streaming API on Vertex AI for building low-latency voice and video AI agents.

Vertex AI Text Embeddings API

Generate text embeddings for semantic search and classification tasks using Google embedding models on Vertex AI.

Firebase AI Logic API

Access Gemini API capabilities through Firebase SDKs for mobile and web applications with built-in security and authentication.

Google Gemini Content Generation API

Generate content using Gemini models with text, image, audio, and video inputs. Supports multimodal prompts, function calling, structured output, and configurable safety settings.

Google Gemini Embeddings API

Generate text embedding vectors for semantic search, classification, clustering, and retrieval tasks using Gemini embedding models.

Scroll within the panel for all 15 ·

Open Collections 1

Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.

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

Google Gemini API

OPEN COLLECTION

Agent Skills 3

An agent skill packages the how-to for driving these APIs from an assistant — the prompts, the sequence, the guardrails — so the knowledge to use the API travels with it.

Packaged agent skills for driving this provider's APIs from an AI assistant.

GraphQL 1

Where a provider ships GraphQL, the schema is the contract. We profile it alongside the REST surface so the whole interface is legible in one place.

GraphQL schemas published by this provider.

Google Gemini GraphQL API

Google Gemini is a family of multimodal AI models (Gemini 1.5 Pro, Flash, Ultra). The Gemini API covers text generation, vision, audio, code generation, embeddings, function cal...

GRAPHQL

Pricing Plans 1

Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.

Published pricing tiers and plan structures.

Rate Limits 1

Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.

Documented rate limits and quota policies.

Google Gemini Rate Limits

7 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.

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

Event Specifications 1

Not every API is request/response. AsyncAPI describes the event-driven and streaming side — the webhooks and channels — so the asynchronous half of the interface is documented the same way the synchronous half is.

AsyncAPI definitions for this provider's event-driven and streaming APIs.

Google Gemini Streaming and Live API

AsyncAPI specification describing Google Gemini's real-time and streaming surface area: * The Live API bidirectional WebSocket service (BidiGenerateContent) used for low-latency...

ASYNCAPI

Semantic Vocabularies 1

JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.

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

Google Gemini Context

0 classes · 23 properties

JSON-LD

Spectral Rules 2

Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.

Google Gemini API Rules

9 rules · 1 errors · 7 warnings

SPECTRAL

Google Gemini API Rules

6 rules · 4 warnings

SPECTRAL

JSON Schema 25

Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.

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

Blob

2 properties

JSON SCHEMA

Candidate

6 properties

JSON SCHEMA

CitationMetadata

1 properties

JSON SCHEMA

CitationSource

4 properties

JSON SCHEMA

Content

2 properties

JSON SCHEMA

ContentEmbedding

1 properties

JSON SCHEMA

EmbedContentRequest

4 properties

JSON SCHEMA

EmbedContentResponse

1 properties

JSON SCHEMA

ErrorResponse

1 properties

JSON SCHEMA

FileData

2 properties

JSON SCHEMA

FunctionCall

2 properties

JSON SCHEMA

FunctionCallingConfig

2 properties

JSON SCHEMA

FunctionDeclaration

3 properties

JSON SCHEMA

FunctionResponse

2 properties

JSON SCHEMA

Google Gemini Generate Content Schema

0 properties

JSON SCHEMA

GenerateContentRequest

7 properties

JSON SCHEMA

GenerateContentResponse

5 properties

JSON SCHEMA

GenerationConfig

11 properties

JSON SCHEMA

Part

5 properties

JSON SCHEMA

PromptFeedback

2 properties

JSON SCHEMA

SafetyRating

3 properties

JSON SCHEMA

SafetySetting

2 properties

JSON SCHEMA

Tool

2 properties

JSON SCHEMA

ToolConfig

1 properties

JSON SCHEMA

UsageMetadata

4 properties

JSON SCHEMA

Scroll within the panel for all 25 ·

JSON Structure 1

JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.

JSON Structure definitions describing this provider's data shapes.

Google Gemini Structure

0 properties

JSON STRUCTURE

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.

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

Google Gemini Authentication

apiKey · 1 scheme

SECURITY

Google Gemini Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Agentic Access 1

An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.

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

Google Gemini Agentic Access

3 operations · 3 acting

3 operations · 3 acting

AGENTIC

Resources

Every other property we hold for Google Gemini — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.

Documentation 1

Reference material describing how the API behaves

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

Build 1

SDKs, sample code, and the tooling you integrate with

Access & Security 2

Authentication, authorization, and security posture

Learn 1

Tutorials, courses, talks, and written guidance

Operate 4

Status, limits, changes, and where to get help

Commercial 2

Pricing, plans, and the legal terms of use

Company 1

The organization behind the API

← All providers · Data indexed from github.com/api-evangelist/google-gemini · machine-readable index on apis.io