Exa MCP Server — AI-Powered Web Search for Every AI IDE

Thu, 16 Apr 2026 00:00:00 +0900

Overview

exa-labs/exa-mcp-server (4,251 stars) is an MCP server that gives AI assistants real-time web search capabilities. It works with virtually every major AI IDE: Claude Code, Cursor, VS Code, Codex, Gemini CLI, Windsurf, Zed, Warp, Kiro, Roo Code, v0, and more. The hosted endpoint at https://mcp.exa.ai/mcp means one URL works everywhere with zero setup.

Architecture

flowchart LR
 A["AI Assistant<br/>Claude, Cursor, etc."] --> B["MCP Protocol"]
 B --> C["Exa MCP Server"]
 C --> D["Web Search"]
 C --> E["Code Search"]
 C --> F["Company Research"]
 D --> G["Clean Results"]
 E --> G
 F --> G
 G --> A

Available Tools

The server exposes three main MCP tools:

web_search_exa — General web search with AI-optimized results
web_fetch_exa — Fetch and extract clean content from any URL
web_search_advanced_exa — Advanced search with filters for domain, date range, and content type

Setup

The easiest path is the hosted MCP endpoint. Just add this URL to your AI IDE’s MCP configuration:

https://mcp.exa.ai/mcp

No local server needed. It works everywhere that supports the MCP protocol.

For self-hosted setups, the TypeScript codebase can be cloned and run locally.

Pre-Built Claude Skills

Exa provides pre-built Claude Skills for common research workflows:

Company research — Deep-dive into any company’s products, funding, team, and tech stack
Competitive analysis — Compare companies across dimensions with real-time data

IDE Support

The breadth of IDE support is impressive. Every major AI coding environment is covered: Cursor, VS Code (Copilot), Claude Desktop, Claude Code, OpenAI Codex, Windsurf, Zed, Warp, Kiro, Roo Code, v0, and more. The hosted MCP approach means adding support for a new IDE is just a configuration change.

Takeaway

Exa MCP Server solves a real pain point: AI assistants that can write code but can’t search the web for current documentation or APIs. The hosted MCP endpoint at a single URL removes the friction of running a local server, making it practical to add web search to any AI workflow.

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