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Search, crawling and research API built for AI agents, with token-efficient results and structured web-data enrichment.
Lightweight MIT-licensed JavaScript chatbot UI widget for building support-agent chat interfaces on top of any LLM.
Open-source data-movement platform now adding a context/action layer for AI agents; 600+ connectors and flexible pricing.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
No public pricing
No public pricing
Free trial available
- ✦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
- ✦MIT-licensed and free to use
- ✦Lightweight (~65kb) JavaScript widget
- ✦4 message display modes plus typewriter effect
- ✦Markdown support and chat history
- ✦Backend hook to integrate any LLM
- ✦Responsive, mobile-friendly, read-only mode
- ✦600+ data connectors
- ✦ELT replication and CDC
- ✦Open-source and managed cloud options
- ✦Airbyte Agents context store (MCP/SDK/CLI)
- ✦Capacity- and volume-based pricing
- ✦Governance: SSO, RBAC, encryption
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- →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
- →Adding an AI chat UI to web apps
- →Building LLM-powered support agents
- →Embedding chat widgets in existing products
- →Prototyping chatbot interfaces
- →Building data pipelines to warehouses
- →Syncing SaaS data for analytics
- →Giving AI agents live business context
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports