AI APIs
AI APIs provide programmatic access to model capabilities — from inference endpoints (OpenAI, Anthropic, Replicate) to specialized services for embeddings, image generation, speech, and more.
Workers AI Provider for the vercel AI SDK
Voyage AI Provider for running Voyage AI models with Vercel AI SDK
Tavily AI SDK tools - Search, Extract, Crawl, and Map
Core TanStack AI library - Open source AI SDK
Adds custom API routes to be compatible with the AI SDK UI parts
A universal LLM client - provides adapters for various LLM providers to adhere to a universal interface - the openai sdk - allows you to use providers like anthropic using the same openai interface and transforms the responses in the same way - this allow
The AI SDK for building declarative and composable AI-powered LLM products.
Forge LLM SDK
The official TypeScript library for the Anthropic Vertex API
The **[xAI Grok provider](https://ai-sdk.dev/providers/ai-sdk-providers/xai)** for the [AI SDK](https://ai-sdk.dev/docs) contains language model support for the xAI chat and completion APIs.
A local development tool for debugging and inspecting AI SDK applications. View LLM requests, responses, tool calls, and multi-step interactions in a web-based UI.
OpenAI's API provides access to GPT-3 and GPT-4 models, which performs a wide variety of natural language tasks, and Codex, which translates natural...
Enterprise B2B company and contact data API.
xAI's Grok API — real-time X data access, Grok-2 generation, vision, OpenAI-compatible.
Enterprise SSO, SCIM, and identity management API.
Enterprise TTS for corporate training and brand voice avatars.
MLOps API for experiment tracking and model management.
Open-source vector DB — built-in vectorizers, hybrid search, GraphQL API, multi-tenancy.
Domain-specific embedding models for RAG.
Instant search engine with vector support.
Low-cost vector database — pay-per-query, S3-backed, up to 10x cheaper at scale.
Open-source model API — Llama, Mixtral, 100+ models, fine-tuning, competitive pricing.
Search API for AI agents — clean web content, answer extraction, designed for RAG and LLM apps.
Enterprise AI presenter video generation API.
Stable Diffusion API for image and video generation.
Stable Diffusion API — image generation, editing, upscaling, SD3/SDXL, video, and 3D models.
Autonomous speech recognition with industry-leading multilingual accuracy.
Search engine scraping API — Google, Bing results as structured JSON with proxy handling.
Game asset generation API with consistent art styles.
Fast Google search results API with geo-targeting.
AI inference on custom RDU chips — high-throughput Llama serving, enterprise deployment.
Gen-3 Alpha video generation API.
Expressive voice AI for narration and audiobooks.
Speech-to-text API built on decade of human transcription data.
Enterprise voice cloning with emotion control and deepfake detection.
AI background removal — instant, high accuracy with hair/transparency, API + integrations.
Multimodal-first API — vision, audio, video understanding across Core/Flash/Edge models.
Professional image generation for design assets.
Rust-based vector search engine — fast, payload filtering, quantization, horizontal scaling.
LinkedIn data extraction API for enrichment workflows.
Multi-modal PII detection and redaction API for 49 languages.
Open-source monetization API for developer tools.
Ultra-realistic AI voice generation — voice cloning from 30s, 142 languages, emotion controls.
AI voice generator with 900+ voices and real-time streaming TTS.
Managed vector database — serverless, auto-scaling, hybrid search, metadata filtering.
Search-augmented LLM API — built-in web search, real-time citations, Sonar models.
OpenAI's managed agent API — persistent assistants with code interpreter, file search, threads.
The most widely used LLM API — GPT-4o, reasoning models, images, audio, embeddings, fine-tuning.
NVIDIA inference microservices — optimized LLM containers, TensorRT-LLM, deploy anywhere.
Open-source embedding models with full transparency.
Scalable experiment tracking and model registry API.
Mistral models API — Large/Small/Codestral, strong efficiency, EU data residency, fine-tuning.
Scalable vector database — billion-scale, GPU acceleration, multiple index types, Zilliz Cloud.
Lightning-fast search engine with vector search.
Dream Machine API for photorealistic video generation.
Ultra-low-latency streaming TTS API for conversational AI.
Document parsing API — complex PDFs with tables and charts to structured markdown for RAG.
All-in-one payments API with global tax compliance.
Serverless embedded vector DB — Lance format, multimodal, versioning, no server needed.
Real-time prompt injection and LLM threat detection API.
Free API to convert URLs to LLM-friendly text — prefix any URL with r.jina.ai for clean content.
High-performance embedding models by Jina.
AI image generation with superior text rendering — logos, posters, designs with accurate text.
AI avatar video generation in 175+ languages.
Ultra-fast LLM API on custom LPU hardware — 500+ tok/s, Llama/Mixtral, OpenAI-compatible.
Google's multimodal API — Gemini 2.5 Pro/Flash, 1M context, video understanding, grounding.
Enterprise audio transcription API with multi-engine accuracy across 100 languages.
Flux image generation models — photorealistic quality, fast inference, available via multiple APIs.
Fast inference API — optimized open-source models, function calling, grammar-based structured output.
API to turn websites into LLM-ready markdown — crawl, scrape, and map with JS rendering.
Serverless inference API with sub-second cold starts.
Neural search API — meaning-based search, full content retrieval, similarity search for AI agents.
Most realistic AI voice API — TTS, voice cloning, 29 languages, streaming, dubbing.
Ultra-realistic AI voice synthesis with cloning and multilingual TTS.
Universal API aggregating 100+ AI providers.
AI web extraction with 10B+ entity knowledge graph.
DeepSeek models API — V3 and R1 reasoning, strong coding, extremely competitive pricing.
Speech-to-text API — Nova-2, real-time streaming, diarization, sentiment, 36+ languages.
Enterprise speech AI with real-time transcription and speaker diarization.
OpenAI's image generator with accurate text rendering and complex compositions.
AI talking head videos and streaming avatars from static images.
AI 3D asset generation with game-ready output from images and text.
ML experiment tracking and model monitoring API.
Enterprise AI API — Command R+ generation, multilingual embeddings, reranking, RAG connectors.
Edge AI inference on Cloudflare — LLMs, images, speech, embeddings at the edge, serverless pricing.
Real-time company and person data enrichment API.
Simple open-source embedding database — add docs, query by text, built-in embeddings, easy RAG.
Fastest LLM inference — 2000+ tok/s on custom wafer-scale chips, Llama models, OpenAI-compatible.
State-space model TTS with ultra-low latency for voice agents.
Independent search API — web, news, images, summarizer, privacy-respecting, free tier.
Azure-managed OpenAI — GPT-4/4o with enterprise security, compliance, and private networking.
AWS managed AI service — Claude, Llama, Mistral via unified API with knowledge bases and agents.
Speech-to-text with intelligence — Universal-2, summarization, PII redaction, LeMUR for audio LLM.
Speech-to-text with audio intelligence, summarization, and PII redaction.
275M+ contacts database API for sales intelligence.
Web scraping platform with 2,000+ ready-made scrapers.
Claude API — Opus/Sonnet/Haiku, 200K context, tool use, computer use, prompt caching.
AWS managed AI agents — action groups, knowledge bases, guardrails, multi-step orchestration.
AI21's Jamba model API with 256K context.
Jamba models API — hybrid SSM-Transformer, 256K context, summarization, enterprise fine-tuning.
What are AI APIs?
AI APIs are the programmatic backbone of AI applications. They provide access to model capabilities (text, image, audio, video generation), specialized services (embeddings, transcription, search), and infrastructure (inference routing, fine-tuning). The landscape includes direct provider APIs (OpenAI, Anthropic, Google), inference platforms (Replicate, Together, Fireworks), and aggregation layers (OpenRouter, LiteLLM).
How to Choose
Match the API to your requirements: latency (real-time vs. batch), cost (per-token vs. per-request vs. flat rate), reliability (SLA, uptime guarantees), and features (streaming, function calling, vision). For production applications, evaluate rate limits, error handling, and failover options. Consider multi-provider setups for resilience.
Key Capabilities to Evaluate
Common Patterns
Call OpenAI, Anthropic, or Google directly. Highest reliability, latest models, but vendor lock-in.
Route through OpenRouter, LiteLLM, or similar. Provider abstraction, fallback routing, but added latency.
Run open models on your infrastructure via vLLM, TGI, or Ollama. Full control, no per-token costs, but requires GPU management.
Run small models at the edge for low-latency use cases. Cloudflare Workers AI, Vercel AI SDK edge runtime.
What to Watch Out For
Top Capabilities
Browse all →Analyzes selected code or entire files and generates natural language explanations of what the code does, how it works, and why certain patterns were chosen. The feature can produce documentation in multiple formats (docstrings, comments, markdown) and supports various documentation styles (JSDoc, Sphinx, etc.). Developers can request explanations at different levels of detail (high-level overview, line-by-line breakdown, architectural context) through the chat interface, with responses appearing as formatted text or code comments.
Translates non-English speech directly to English text using the same Transformer encoder-decoder architecture by prepending a 'translate' task token during decoding, bypassing explicit transcription. The AudioEncoder processes mel spectrograms identically to transcription, but the TextDecoder generates English tokens directly from audio embeddings. This end-to-end approach avoids cascading errors from intermediate transcription-then-translation pipelines and enables language-agnostic audio understanding.
Detects the spoken language in audio by analyzing the AudioEncoder embeddings and using the TextDecoder to predict a language token before generating transcription text. Language detection is implicit in the multitask training; the model learns to identify language from acoustic features without a separate classification head. Supports 99 languages with varying confidence based on training data representation (English: 65% of training data, others: 0.1-2%).
Maintains conversation history within a single chat session, allowing developers to ask follow-up questions, request refinements, and build on previous responses without re-providing context. The extension manages conversation state (messages, responses, context) and sends the full conversation history to ChatGPT's API with each request, enabling contextual understanding of refinement requests like 'make it faster' or 'add error handling'.
Generates new code snippets based on natural language descriptions by sending the user's intent and current editor selection context to OpenAI's API, then inserting the generated code at the cursor position or displaying it in the sidebar. The extension reads the active editor's selected text to provide code context, enabling the model to generate syntactically appropriate code for the detected language. Generation is triggered via keyboard shortcut (Ctrl+Alt+G), command palette, or toolbar button.
Generates docstrings, comments, and API documentation for functions, classes, and modules by analyzing code structure and semantics using GPT-4o. The extension detects function signatures, parameter types, and return types, then generates documentation in multiple formats (JSDoc, Python docstrings, Javadoc, etc.) matching the language and project conventions. Generated docs are inserted inline with proper indentation and formatting.
Analyzes staged or modified code changes in the current Git repository and generates descriptive commit messages using the configured AI provider. The feature integrates with VS Code's Git context to identify changed files and diffs, then sends this information to the AI model to produce commit messages following conventional commit formats or project-specific conventions. This automation reduces the cognitive load of writing commit messages while maintaining code quality and repository history clarity.
Offers a freemium pricing structure where basic problem detection and explanations are available for free, with premium features (likely advanced fix generation, priority support, or higher API quotas) available through paid subscription. The free tier includes GNN-based problem detection and LLM-powered explanations using Metabob's default backend, while premium tiers likely unlock OpenAI ChatGPT integration, higher analysis quotas, or team features. Pricing details are not publicly documented in the marketplace listing.
Browse Other Types
Autonomous AI systems that act on your behalf
ModelsFoundation models, fine-tunes, and specialized AI models
MCP ServersModel Context Protocol tools and integrations
RepositoriesOpen-source AI projects on GitHub
ExtensionsBrowser and IDE extensions powered by AI
WorkflowsAutomation sequences and AI pipelines
View all 14 types →Frequently Asked Questions
What is the cheapest AI API for text generation?
For high-volume text generation, self-hosted open models (via vLLM or Ollama) eliminate per-token costs. Among hosted APIs, together.ai and groq offer competitive pricing for open models. For proprietary models, GPT-4o Mini and Claude Haiku offer strong capability at low cost.
How do I handle AI API rate limits in production?
Implement exponential backoff with jitter, use request queuing with concurrency limits, consider multi-provider failover (OpenRouter or custom routing), and cache common responses. For high-volume use cases, request rate limit increases from providers early.