How to Install Exa MCP in OpenAI Agents SDK

Neural search for AI agents — search by meaning, find similar content, and get research-grade web results

What Exa MCP does

Exa is the search API designed from the ground up for AI and semantic search. Unlike traditional keyword search, Exa understands meaning — finding conceptually related content even without matching keywords. Features: - Neural search — finds content by meaning, not just keywords - Find similar pages to any URL - Research mode — comprehensive, multi-source research synthesis - Date-filtered search for recent content - Domain-specific search (academic papers, news, GitHub, etc.) - Structured content extraction with highlighted passages - Competitor research and landscape analysis - Technical documentation search Where Exa wins over Brave/Tavily: - "Find papers similar to this arXiv abstract" — understands semantic similarity - "Find companies doing what Figma does but for 3D" — finds conceptual matches - "What was written about [topic] before 2023?" — precise temporal filtering Exa is the choice for research-intensive AI workflows where query precision matters.

exa

semantic

neural

research

Installation steps

1Install: pip install openai-agents
2Copy the snippet below into your agent code
3Replace placeholder env values with your real keys
4Pass mcp_servers=[mcp_server] to your Agent()

Python snippet

Python snippetpython

from agents import Agent
from agents.mcp import MCPServerStdio

mcp_server = MCPServerStdio(
    command="npx",
    args=["-y", "exa-mcp-server"],
    env={
        "EXA_API_KEY": "your_exa_api_key",
    },
)

agent = Agent(
    name="My Agent",
    model="gpt-4o",
    mcp_servers=[mcp_server],
)

Full server details GitHub Open Config Editor

Install in other clients

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For maintainers

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