Exa is a neural search engine built for finding information by meaning rather than just matching keywords. Search the web for relevant articles, research papers, company information, code, and news; extract clean content from webpages; find similar links; and retrieve structured results with source metadata for research and AI applications.
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Encrypted at rest, isolated from the model
Resolved from an AES-256-GCM vault at the moment of the call and attached to the request — the model never sees the secrets.
Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.
Read a webpage's full content as clean markdown. Use after web_search_exa when highlights are insufficient or to read any URL. Best for: Extracting full content from known URLs. Batch multiple URLs in one call. Returns: Clean text content and metadata from the page(s).
Start or resume an Exa Agent run for multi-step research, list-building, or enrichment. Use it instead of running many searches yourself when a task needs multiple searches, cross-source verification, or a structured table of results. Long-running: returns a run ID; resume with runId when the tool reports the run is still running. Not for a single question or lookup (use web_search_exa) or reading a known URL (use web_fetch_exa). An interrupted tool call is not an explicit cancellation request.
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Discovery, routing, credentials, tool scoping and execution logs all happen at the gateway→connections stay ACTIVE with no work from you
Exa MCP runs through a gateway that holds the credentials, scopes the access and records every call.
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