Building web search-enabled agents with Strands and Exa

This post is co written by Ishan Goswami and Nitya Sridhar from Exa.

If you are building web search-enabled AI agents for research, fact-checking, or competitive intelligence, access to current and reliable information is critical. Most general-purpose search APIs are not designed for agent workflows. They return HTML-heavy pages and short snippets optimized for human browsing, not structured data that an agent can directly consume. As a result, developers often need to build additional layers, custom crawlers, parsers, and ranking logic, to transform this content into something usable within an agent workflow.

The Exa integration for the Strands Agents SDK addresses this gap with an AI-native search and retrieval layer built directly into the tool interface. Exa delivers clean, structured content formatted for direct use in LLM context windows, without requiring post-processing to strip markup or reformat output. Combined with the Strands Agents SDK’s model-driven architecture, where the model ...