exa-labs/exa-mcp-server

Exa MCP for web search and web crawling!

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Summary Information

Updated 36 minutes ago
Added to GitGenius on September 13th, 2026
Created on November 27th, 2024
Open Issues & Pull Requests: 47 (+0)
GitHub issues: Enabled
Number of forks: 391
Total Stargazers: 5,003 (+0)
Total Subscribers: 24 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 8.7 days
Mean response time: 34.5 days
90th percentile: 102.6 days
Tracked items: 98

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 13% of issues opened in the past year have been closed. Three people close 81% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 27
New in 7 days: 4
Closed in 7 days: 0
Avg open age: 50 days
Stale 30+ days: 14
Stale 90+ days: 7

Recent activity

Opened in 7 days: 3
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Exa MCP Server is a Model Context Protocol server that connects AI agents to Exa's web search and content fetching capabilities.

The tool solves the problem of giving AI agents access to current web information and the ability to perform multi-step research tasks. It works by exposing Exa's search and crawling APIs through the Model Context Protocol, allowing compatible AI applications to invoke web search, retrieve page content, and conduct iterative research workflows without leaving the agent's execution environment.

Developers should adopt this tool if they are building AI agents or applications that need real-time web access and research capabilities. It suits projects where an AI system must gather current information, verify facts, or explore topics across multiple web sources. The tool integrates directly with Cursor, VS Code, Claude, and ChatGPT, making it immediately available in popular development and AI chat environments. No comparison to alternative tools is provided in the README.

The project maintains active integration with multiple major AI platforms and development tools, indicating ongoing effort to keep the server compatible with evolving standards and client applications. Development appears focused on expanding the ecosystem of supported clients rather than adding new core search or crawling features.