How to Use the Exa AI MCP in CrewAI

Deploy specialized search agents with CrewAI and this MCP Server for autonomous web operations.

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Connect Exa AI MCP to CrewAI

Create your Vinkius account to connect Exa AI to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Exa AI with CrewAI

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Perplexity

Role-based search collaboration

Assign `search_web` to a researcher agent while your analyst agent uses `get_contents` to evaluate the findings. This separation ensures each agent focuses on its specific task. Your crew shares the memory of these searches. This allows one agent to build on the work of another without needing to repeat the query.

Autonomous discovery pipelines

Set up a crew that uses `search_with_contents` to scan for new information and `find_similar` to expand the scope. It runs entirely on its own once you define the goal. This is best for ongoing monitoring tasks. The agents handle the search, the retrieval, and the follow-up without you needing to check in.

Selective tool exposure

Use a tool filter to give specific agents access only to the tools they need. Your research agent gets `search_web`, while your summarizer only gets `get_contents`. This keeps your agents efficient. It prevents them from using tools that aren't relevant to their specific role in the crew.

Setup guide

Set up Exa AI MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Exa AI tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Exa AI Analyst",
    goal="Access and analyze Exa AI data via MCP.",
    backstory="Expert analyst with direct Exa AI access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Exa AI transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Exa AI Analyst",
        goal="Access and analyze Exa AI data via MCP.",
        backstory="Expert analyst with direct Exa AI access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Exa AI transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Exa AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Exa AI MCP in CrewAI

Pass the server URL to the agent's mcps parameter. The framework will automatically register the tools so the agent can invoke them during its task.

Yes. CrewAI uses a shared memory space, so any data retrieved by one agent is available to the rest of the crew for their analysis.

It is. The tool set is designed for programmatic access, making it a reliable source of information for agents that need to work without human oversight.

Data security is handled at the transport layer. The server does not persist your search logs, and all communication is encrypted during the session.

You can use a tool filter to restrict the agent's access. This ensures the agent can only perform the specific search operations you authorize.

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