Search the web, extract content, and fetch URLs in Convex functions using Exa's AI-powered search API for building intelligent agents and RAG systems.
npm install @exalabs/convex-exaThe Exa component brings real-time web intelligence to Convex applications through the Exa API. It provides three core functions: web search with optional highlights, structured deep search, and direct URL content fetching. Developers can power AI agents, research workflows, content monitoring, and knowledge-base updates with fresh web context in just a few backend calls.
The Exa component enables web searching directly from Convex actions using semantic AI queries. You can search for relevant content, get clean results, and process web data within your Convex backend for AI agents or research features.
Exa provides content extraction capabilities that fetch and clean web page content for RAG systems. This allows you to retrieve structured data from URLs and store it in your Convex database for vector search and AI applications.
The Exa component gives AI agents access to live web data through semantic search and URL fetching. Agents can research topics, gather current information, and make decisions based on real-time web content within your Convex functions.
Exa integrates web search and content extraction into Convex actions, enabling applications to access current web information. This supports use cases like competitive research, content aggregation, and knowledge base enrichment with live data.
The Exa component supports semantic AI-powered web searches that understand intent and context rather than just keyword matching. It's designed for finding relevant, high-quality content for AI applications, research, and knowledge extraction rather than traditional search engine results.
The Exa component provides URL fetching and content extraction capabilities that return clean, structured content suitable for AI processing. The extraction focuses on main content and removes navigation, ads, and other page elements to provide usable data for RAG and agent systems.
After performing searches or content extraction with the Exa component in Convex actions, you can store the results in your Convex database using mutations. This enables you to build searchable knowledge bases, cache research results, or feed data into vector search systems.
The Exa component uses AI-powered semantic search to find relevant content rather than scraping predetermined websites. It provides clean, structured results optimized for AI consumption, handles content extraction automatically, and focuses on finding the most relevant information for specific queries.