How to Use the Dades Obertes Catalunya MCP in CrewAI

Deploy specialized agent teams to research and analyze Catalonian public records autonomously with CrewAI.

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Connect Dades Obertes Catalunya MCP to CrewAI

Create your Vinkius account to connect Dades Obertes Catalunya 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 Dades Obertes Catalunya with CrewAI

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Perplexity

Multi-agent search and query coordination

Let one agent find the data while another analyzes it. In CrewAI, you can assign a Researcher agent to run `search_catalog` and find relevant database IDs for Catalonia public services. Once found, the Researcher passes those IDs to an Analyst agent. That Analyst then runs `query_dataset` to pull the raw numbers, keeping tasks clean and specialized.

Hierarchical data extraction with this MCP Server

Build a structured team with a manager agent overseeing the data extraction. The manager decides when to trigger SoQL queries based on the project goals you set. If a query returns messy data, the manager agent instructs the analyst to refine the `$where` parameters and run `query_dataset` again, ensuring high-quality final reports.

Shared memory for complex Catalonian history

CrewAI agents share context across tasks. If an agent queries a transport dataset, other agents remember those results when analyzing related environmental databases. This prevents redundant calls to the Catalonian open data portal. Your crew builds a cohesive picture of the region's public records without hitting API limits.

Setup guide

Set up Dades Obertes Catalunya 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 Dades Obertes Catalunya tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Dades Obertes Catalunya 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 Dades Obertes Catalunya. 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 Dades Obertes Catalunya MCP in CrewAI

Pass the Vinkius URL directly in your Agent's mcps array. CrewAI automatically discovers search_catalog and query_dataset, making them available to that specific agent.

Yes. You can share the MCP Server across your entire crew or restrict it to a single researcher agent to keep your data gathering structured.

Your agents use their reasoning capabilities to construct valid SoQL parameters like $select and $where. They pass these directly to query_dataset to pinpoint the exact records needed.

Yes, you can use CrewAI's tool filtering to ensure only your analyst agent can execute database queries, while other agents focus on writing reports.

Your SoQL queries and retrieved Catalonian public datasets are held strictly within your local CrewAI process memory. No data is cached or exposed to third parties during the execution of your crew's tasks.

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