Exa MCP Server
Officialby Exa Labs
Exa is a search engine built specifically for AI — not humans. Unlike Google, which ranks pages by popularity and backlinks, Exa uses neural/semantic search to understand the meaning behind a query and return the most relevant content for machine consumption. Its API returns clean, structured text rather than HTML-heavy pages, making it ideal for feeding context into large language models. The Exa MCP Server exposes Exa's full search platform directly inside any MCP-compatible AI assistant or agent framework. Once installed, agents gain access to real-time web search, code context retrieval, company intelligence, deep research workflows, full-page crawling, and people/professional profile discovery — all through natural language tool calls. What sets Exa apart for AI developers is its combination of speed (sub-180ms latency), accuracy (outperforms competitors on FRAMES and Tip-of-Tongue benchmarks), and token efficiency (highlights reduce LLM costs by over 50%). The server ships with three tools enabled out of the box — general web search, code context from GitHub and Stack Overflow, and company research — while advanced tools like deep researcher agents, domain-filtered search, and people search can be unlocked as needed. Exa is SOC 2 Type II certified and supports zero data retention for privacy-sensitive workloads. A generous free plan is available, with API keys obtainable from the Exa dashboard.
Installation
Key Features
- ✓Real-time web search with clean, LLM-ready content via web_search_exa
- ✓Code context retrieval from GitHub, Stack Overflow, and technical docs
- ✓Company research tool for business intelligence, news, and organizational insights
- ✓Deep researcher agent for multi-step report generation
- ✓Full webpage crawling for extracting complete page content from any URL
- ✓Sub-180ms response latency with token-efficient highlights that cut LLM costs by 50%+
Use Cases
- →Giving AI coding assistants up-to-date documentation, Stack Overflow answers, and GitHub examples during development
- →Powering autonomous research agents that need to gather, synthesize, and report on real-world information
- →Enriching CRM or sales workflows by pulling live company intelligence and news into agent pipelines
- →Building RAG pipelines that require fast, accurate, structured web content
- →Competitive analysis and market research by querying specialized finance, news, and recruiting indexes