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Search, crawling and research API built for AI agents, with token-efficient results and structured web-data enrichment.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
Human-friendly API testing client for terminal, desktop and web, known for readable syntax; the CLI is open source.
AI-powered code editor with agentic workflows for developers.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦Web search API tuned for agents
- ✦Full-page contents with token-efficient highlights
- ✦Asynchronous agents for deep research and enrichment
- ✦Structured outputs with grounded citations
- ✦Web monitors that track new events on a schedule
- ✦Zero data retention and SOC 2 Type II controls
- ✦Single OpenAI-compatible API for 500+ models
- ✦Chat, image, video and audio models
- ✦Discounted per-request pricing
- ✦One dashboard for keys, quotas and usage
- ✦Multi-region routing and failover (99.9% uptime)
- ✦Multiple payment methods incl. crypto
- ✦Human-friendly command-line HTTP client
- ✦Web and desktop GUI apps
- ✦Simple, readable request syntax
- ✦Request export/import and history
- ✦Path parameters and 'copy as command'
- ✦Open-source terminal version
- ✦AI-powered code completion and suggestions
- ✦Automated lint fixing
- ✦Cascade agent for advanced coding assistance
- ✦Integrated app building and deployment
- ✦MCP server support for custom tools
- ✦Terminal command integration
- ✦Memory of codebase structure and workflow
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- →Give coding agents current docs and repo context
- →Power chatbots with real-time web answers
- →Enrich company and people data at scale
- →Monitor the web for fresh events
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
- →Testing REST APIs
- →Sending and inspecting HTTP requests
- →Debugging web services
- →Sharing API requests across a team
- →Accelerating software development by automating repetitive tasks
- →Reducing onboarding time for new developers
- →Improving code quality and reducing tech debt
- →Streamlining the app building and deployment process
- →Enhancing developer productivity by keeping them in a state of flow
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts