Exa MCP Server

Web search, code search, and company research for AI assistants over MCP

Freemium· Free: $0 USD · Team: $4 USD per user/month · Enterprise: $21 USD per user/monthMCP ServersExa neural search index (in-house)

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Best for

Developers wiring live web search into Claude Desktop, Cursor, or Claude Code, and teams building research/RAG agents that need a clean, LLM-tuned retrieval layer without running their own scraping stack.

Skip if

Hobbyists who want a fully free forever tool, high-volume production workloads sensitive to per-query cost, or use cases needing authenticated or JavaScript-heavy pages Exa's crawler can't reach.

Exa MCP Server is the official Model Context Protocol connector for Exa, a neural search engine built specifically for AI agents. It plugs an LLM client (Claude Desktop, Cursor, Claude Code, VS Code, Windsurf, Zed, Warp, LM Studio, Replit, Roo Code, Kiro and any other MCP-compliant host) into Exa's live web index so the model can run real-time searches, fetch full page contents, and do multi-step research without you having to build the retrieval layer yourself. The server ships two tools by default (web_search_exa for general search and web_fetch_exa for known-URL content extraction) and exposes a menu of optional tools you can toggle: web_search_advanced_exa with domain/date/text filters, an agent_run tool for multi-step research and structured enrichment, plus category-specific searches for companies, publications, financial reports, personal sites, and people. It's distributed as a hosted HTTP endpoint (mcp.exa.ai/mcp) so most users skip local installation entirely - drop the URL into your client's MCP config, paste an API key or use OAuth, and the tools appear in your assistant. The typical workflow is 'grounded' generation: an agent decides it needs current information, calls web_search_exa, gets clean markdown snippets, optionally follows up with web_fetch_exa on the most promising hits, and cites what it used. Because Exa's semantic index is designed for LLM consumption (not SEO pages), results tend to be denser and more relevant than what you get by proxying Google. It's a strong default retrieval layer for anyone building research agents, RAG-style workflows, or a Claude/Cursor setup that needs live web context.

Editor's take

This is the retrieval MCP I reach for first. The hosted endpoint sidesteps every 'why is my local MCP crashing' headache, results are noticeably cleaner than a Google-wrapper, and the pricing is honest. Keep an eye on the meter if you let agents loose with Deep Search - that's where surprise bills come from - but for most day-to-day 'give my assistant the live web' work, it's the shortest path from zero to working.

— The AI Tool Bible editorial team

Pros

✅ Hosted HTTP endpoint means no local install, no Node process to babysit, works instantly across every major MCP client
✅ Neural/semantic search is tuned for LLM consumption - cleaner snippets and better relevance than wrapping a general web search API
✅ Rich tool set beyond plain search: full-page fetch, category filters (company/paper/personal/financial), and a multi-step agent tool
✅ Pay-as-you-go with a real free tier ($20 signup credit plus $10/month) makes it low-friction to trial
✅ MIT licensed, transparent tool definitions on GitHub, and OAuth support for shared team environments
✅ Officially maintained by Exa Labs and actively updated, with pre-built Claude Skills for specialized workflows

Cons

⚠️ Costs stack quickly on high-volume agents - Deep Search at $12-15 per 1k and Agent runs up to $1 each can dwarf model token costs
⚠️ Requires an Exa account and API key (or OAuth) - not a truly free option beyond the monthly credit
⚠️ Documented quirks: multi-item arrays in text filters return 400s, and some categories silently disallow domain/date filters
⚠️ Some authentication-gated content still needs a browser-based fallback the server can't provide
⚠️ Search quality is only as good as Exa's index - niche or very fresh content may be missing versus Google or Bing

Use cases

Live web search inside Claude DesktopRAG grounding for research agentsCompany and competitor researchFinancial report discoveryAcademic paper and publication lookupPeople and personal-site profilingFull-page content extraction for summarizationMulti-step deep research via agent_runCoding assistants that need current library docsCursor and VS Code AI workflows