Exa vs Apify
Exa MCP and Apify MCP are both in the search-and-data category, but they solve different problems and should not be treated as interchangeable. Exa is an AI-native search engine: its three tools (web_search_exa, web_fetch_exa, web_search_advanced_exa) let an agent search the live web and retrieve clean, ready-to-use content for a known URL, with the advanced tool adding domain, date, and content filters. Apify is a cloud platform for web scraping and automation: its server exposes tools to search the Apify Store for a ready-made scraper Actor (search-actors), inspect its input schema (fetch-actor-details), run it (call-actor), register it as a dedicated tool for the session (add-actor), monitor and abort runs (get-actor-run, get-actor-run-list, get-actor-log, abort-actor-run), and read results from datasets and key-value stores (get-dataset-items, get-dataset-schema, get-key-value-store-record). The distinction matters: Exa answers queries across the open web in real time; Apify runs pre-built scrapers on specific targets and returns structured output.
How they compare
| Dimension | Exa | Apify |
|---|---|---|
| Core job | Real-time AI web search: find relevant sources for a query and return their clean text content, or fetch a known URL. No scraping infrastructure, no persistent runs. | Scraping and automation via cloud-hosted Actors: discover a scraper in a catalog of 6,000+, run it against a target, and read structured results from a dataset or key-value store. |
| Tool count and shape | Three focused tools: web_search_exa (general search), web_fetch_exa (fetch a known URL), and web_search_advanced_exa (filtered search by domain, date, and content type). | Nineteen tools covering Actor discovery, invocation, run lifecycle management (get-actor-run, get-actor-log, abort-actor-run), dataset retrieval (get-dataset-items, get-dataset-schema), key-value store access, and documentation search. |
| Result latency and output form | Near-instant: web_search_exa returns clean, LLM-ready content from the current web in a single synchronous call. No run management needed. | Asynchronous by design: call-actor starts a run; the agent then polls with get-actor-run and reads results with get-dataset-items or get-key-value-store-record once the run completes. |
| Coverage and targeting | Covers the open web broadly with a neural index; web_search_advanced_exa can constrain to specific domains and date ranges for tighter retrieval. | Targets specific sites with site-specific Actors (e.g., a LinkedIn scraper, an Amazon product scraper). Breadth depends on which Actors exist in the Store rather than a single index. |
| Best-fit task | Research, discovery, and grounding: finding the best current sources for a question and getting readable content back without any scraping infrastructure. | Structured data extraction from known targets: scraping a product catalog, pulling social media posts, or running a site-specific automation that returns typed records in a dataset. |
Verdict
These two tools rarely compete for the same task. Reach for Exa when an agent needs to search the open web, get clean content for a question, or fetch a known URL without any run management overhead. Reach for Apify when the target is specific, a ready-made Actor exists for it, and you want structured output in a dataset rather than raw page text. Exa answers questions across the web in one synchronous call; Apify runs site-specific scrapers as asynchronous jobs and returns typed records. Many pipelines use both: Exa to discover what to target, Apify to extract structured data from those targets at scale.
FAQ
- Which is better for real-time news or current-events questions?
- Exa. Its web_search_exa tool searches the live web and returns ready-to-use content tuned for LLMs, and web_search_advanced_exa can filter by date to surface recent results. Apify Actors are designed for scraping known sites on demand rather than broad current-events retrieval.
- Do both support remote hosted endpoints?
- Yes. Exa offers a hosted remote endpoint at https://mcp.exa.ai/mcp (bearer API key auth). Apify offers a hosted Streamable HTTP endpoint at https://mcp.apify.com with OAuth support for clients like Claude and VS Code, plus bearer token auth. Both also have local stdio packages.