Exa Search MCP Server

Introduction

The Exa MCP server provides AI agents with powerful web search and content extraction capabilities, built specifically for AI-driven workflows. Developed by Exa (exa.ai), this server offers one unified API for search, crawling, and research, trusted by teams at Cursor, HubSpot, Databricks, and Cognition.

The server exposes two complementary tools: web_search_exa for finding current information across any topic using semantically rich natural language queries, and web_fetch_exa for reading full webpage content as clean markdown. Together, these tools enable agents to retrieve token-efficient, ready-to-use content with clean text extraction from top search results.

Exa is designed to make agents smarter by providing comprehensive coverage across multiple search verticals—including general web, company, people (LinkedIn profiles), and code searches. With features like highlights for token reduction and specialized category filtering, it's ideal for grounding agent responses in accurate, current, and cited information.

Use Cases

1. Current Events & News Research Agents can search for the latest developments on any topic and pull the most relevant, up-to-date information.

   • Sample prompt: Find the latest news about Nvidia's newest GPU releases and summarize the key announcements from the past month.

2. Company & Market Research Using the category:company filter, agents can research businesses, competitors, and market landscapes.

   • Sample prompt: Search for European Series B fintech companies with 50+ employees that raised funding recently, and give me details on each.

3. People & Talent Sourcing The category:people filter allows searching LinkedIn-style profiles for recruiting or networking purposes.

   • Sample prompt: Find profiles of senior machine learning engineers based in San Francisco who have experience at large AI labs.

4. Deep Content Extraction from Specific URLs After finding relevant results, agents can fetch full page content as clean markdown for detailed analysis.

   • Sample prompt: Read the full content of this article at https://example.com/ai-report-2025 and give me a detailed breakdown of the main findings.

5. Fact-Checking & Answering Questions Agents can verify claims or answer factual queries with grounded citations from top sources.

   • Sample prompt: Who is the current CEO of Boeing and when was the company founded? Provide sources.

6. Technical Documentation & Code Research Search across docs and repositories for token-efficient answers to programming questions.

   • Sample prompt: Find documentation and code examples comparing React and Vue performance for large-scale applications.

7. Multi-Source Content Aggregation Combine both tools to search broadly then batch-fetch multiple URLs for comprehensive research.

   • Sample prompt: Search for the top 5 articles comparing electric vehicle battery technologies, then read all of them and create a comparison table.

8. Competitive Intelligence & Enrichment Gather structured data across companies for lead generation and market analysis.

   • Sample prompt: Find the top aerospace companies, then read their about pages to extract each company's CEO name and founding year.