How to Use the Europeana MCP in CrewAI

Deploy autonomous research crews using CrewAI and the Europeana MCP Server.

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Connect Europeana MCP to CrewAI

Create your Vinkius account to connect Europeana 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 Europeana with CrewAI

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Collaborative research with CrewAI

Assign a dedicated agent to handle `search_records` while another agent focuses on interpretation. CrewAI allows these agents to share memory and build a knowledge base together. This setup removes the need for you to manage individual tool calls. The crew handles the search-and-fetch cycle autonomously.

Deep record analysis within CrewAI

Task your agents with fetching individual artifact details via `get_record`. CrewAI agents can compare these records to build reports or summarize museum collections. They work through the list of items you provide, ensuring every record is processed. It turns a manual research task into a background operation.

Bulk metadata harvesting for CrewAI

Use `oaipmh_request` to feed your agents large sets of raw metadata. This provides the context they need to perform broad, historical analysis across thousands of items. Your agents can parse these files and extract specific patterns. It is the fastest way to get your crew the data they need to start working.

Setup guide

Set up Europeana 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 Europeana tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Europeana 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 Europeana. 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 Europeana MCP in CrewAI

Yes, the shared memory feature allows agents to pass findings from one to another. One agent can find the records and another can refine the data.

You simply add the server URL to the agent's MCP configuration. The framework handles the connection and exposes the tools automatically.

You can use a tool filter to limit which agents have access to which tools. This prevents agents from accidentally running large bulk requests.

They are built for consistent, machine-readable output. This stability is required for agents to operate without human intervention.

Security is managed through the isolated server endpoint. Only the specific record identifiers and search parameters are transmitted, ensuring no sensitive credentials leak during the agent's autonomous operations.

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