How to Use the Datos Abiertos Castilla-La Mancha MCP in CrewAI

Deploy a crew of specialized AI agents to analyze Castilla-La Mancha public data using CrewAI.

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Connect Datos Abiertos Castilla-La Mancha MCP to CrewAI

Create your Vinkius account to connect Datos Abiertos Castilla-La Mancha 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 Datos Abiertos Castilla-La Mancha with CrewAI

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Perplexity

Multi-Agent Regional Research

CrewAI shines when you divide and conquer. Assign one agent to search the Castilla-La Mancha portal using `list_datasets` and another to inspect specific files with `get_resource`. The agents share memory and pass findings back and forth. This collaborative approach lets them piece together complex regional insights without human hand-holding.

Deep Database Mining via MCP Server Tools

Querying municipal data requires deep drilling. Your specialized research agent can run `search_datastore` to extract specific rows from Castilla-La Mancha's public tables. Once the data is pulled, a separate analyst agent can parse the results, calculate statistics, and generate reports based on the raw records.

Dynamic Tag and Topic Mapping

Let your agents use this MCP connection to map out regional trends by analyzing portal categories. Using `list_tags`, your crew can identify which public sectors are publishing the most data. They can cross-reference these tags with individual datasets via `get_dataset` to build a structured map of Castilla-La Mancha's open data ecosystem.

Setup guide

Set up Datos Abiertos Castilla-La Mancha 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 Datos Abiertos Castilla-La Mancha tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Datos Abiertos Castilla-La Mancha 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="Datos Abiertos Castilla-La Mancha Analyst",
        goal="Access and analyze Datos Abiertos Castilla-La Mancha data via MCP.",
        backstory="Expert analyst with direct Datos Abiertos Castilla-La Mancha access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Datos Abiertos Castilla-La Mancha 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 Datos Abiertos Castilla-La Mancha. 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 Datos Abiertos Castilla-La Mancha MCP in CrewAI

You can pass the Vinkius server URL directly to your CrewAI agent configuration using the MCP list. For advanced setups, use the HTTP server class to filter specific tools.

Yes. CrewAI's shared memory allows different agents to invoke tools like `search_datastore` and share the resulting data across the entire execution pipeline.

Yes. You can set up a hierarchical or sequential crew where Agent A finds resources using `list_datasets`, and Agent B processes them using `get_resource`.

The framework manages the underlying MCP transport layers automatically, ensuring stable communication between your agent crew and the public endpoints.

Yes. Vinkius runs the server in an ephemeral, isolated environment. Only the specific public dataset metadata and datastore records are retrieved, with zero logging of your internal prompts.

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