Google Gemini
Google's multimodal AI model APIs for text, image, audio, and video understanding.
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.
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.
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 COLLECTIONAgent 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...
GRAPHQLPricing 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
RATE LIMITSFinOps 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.
Google Gemini Finops
FINOPSEvent 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...
ASYNCAPISemantic 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
JSON-LDSpectral 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
SPECTRALGoogle Gemini API Rules
SPECTRALJSON 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
JSON SCHEMACandidate
JSON SCHEMACitationMetadata
JSON SCHEMACitationSource
JSON SCHEMAContent
JSON SCHEMAContentEmbedding
JSON SCHEMAEmbedContentRequest
JSON SCHEMAEmbedContentResponse
JSON SCHEMAErrorResponse
JSON SCHEMAFileData
JSON SCHEMAFunctionCall
JSON SCHEMAFunctionCallingConfig
JSON SCHEMAFunctionDeclaration
JSON SCHEMAFunctionResponse
JSON SCHEMAGoogle Gemini Generate Content Schema
JSON SCHEMAGenerateContentRequest
JSON SCHEMAGenerateContentResponse
JSON SCHEMAGenerationConfig
JSON SCHEMAPart
JSON SCHEMAPromptFeedback
JSON SCHEMASafetyRating
JSON SCHEMASafetySetting
JSON SCHEMATool
JSON SCHEMAToolConfig
JSON SCHEMAUsageMetadata
JSON SCHEMAScroll 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
JSON STRUCTURESecurity 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.
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.
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
Other 3
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/google-gemini · machine-readable index on apis.io