How to Use the Linkup (AI Search & RAG) MCP in CrewAI

Give your CrewAI crew real-time web intelligence. Linkup (AI Search & RAG) empowers your autonomous agents to research on the fly.

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Connect Linkup (AI Search & RAG) MCP to CrewAI

Create your Vinkius account to connect Linkup (AI Search & RAG) 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 Linkup (AI Search & RAG) with CrewAI

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Deploy research agents with CrewAI

Assign `search_web` to a dedicated research agent in your crew. It will perform real-time queries to gather facts for the rest of your agents. You can limit which agents have access to the tool. This keeps your research contained while your other agents focus on synthesis and action.

Parse web content using `fetch_url`

Your CrewAI agents can use `fetch_url` to grab the content of a specific page. This is useful when your research agent finds a source that needs closer reading. It handles the heavy lifting of parsing dynamic sites. Your agents receive the text ready for analysis without needing their own browser engine.

Scale autonomous operations

This MCP Server scales with your CrewAI setup. You can run multiple agents hitting the API concurrently to speed up your research phase. It removes the need for custom scraping code in your agents. You just define the tool and let your crew manage the research process.

Setup guide

Set up Linkup (AI Search & RAG) 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 Linkup (AI Search & RAG) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Linkup (AI Search & RAG) 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="Linkup (AI Search & RAG) Analyst",
        goal="Access and analyze Linkup (AI Search & RAG) data via MCP.",
        backstory="Expert analyst with direct Linkup (AI Search & RAG) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Linkup (AI Search & RAG) 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 Linkup. 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 Linkup (AI Search & RAG) MCP in CrewAI

Pass the server URL to your agent's MCP configuration. The agent will then gain the ability to call the search tool when needed.

Yes. Shared memory allows your agents to pass search results from one member to the next for deeper analysis.

It does. You can set up a manager agent to delegate search tasks to specialized agents using the MCP tools.

Your queries are encrypted in transit and processed in a secure V8 sandbox. We do not persist your search history.

It processes public HTML, text, and metadata from web pages. Your private agent memory and task data stay on your local machine.

Use it with your favorite AI tools

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