How to Use the Comunidad de Madrid (Portal Regional) MCP in CrewAI

Deploy autonomous crews to analyze Comunidad de Madrid (Portal Regional) data with CrewAI.

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Connect Comunidad de Madrid (Portal Regional) MCP to CrewAI

Create your Vinkius account to connect Comunidad de Madrid (Portal Regional) 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 Comunidad de Madrid (Portal Regional) with CrewAI

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Multi-agent Teams for Comunidad de Madrid (Portal Regional)

Assign one agent to `search_datasets` and another to analyze the output. CrewAI coordinates the handoff so your team works in sequence. Your agents share memory, allowing them to build a full picture of regional activity. They collaborate to extract insights from the portal without your manual input.

Autonomous Regional Monitoring

Set a moderator agent to watch for updates using `list_datasets`. When it spots a change, it triggers the rest of your crew to act. This setup keeps your operations running 24/7. Your agents handle the repetitive tasks of checking the Comunidad de Madrid (Portal Regional) portal for you.

Specialized Agent Tasks

Filter which tools each agent uses to keep them focused. Give your researcher access to `get_dataset` while your action-agent uses `search_datastore`. This keeps your CrewAI setup efficient. Each agent only sees the tools it actually needs to perform its specific role.

Setup guide

Set up Comunidad de Madrid (Portal Regional) 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 Comunidad de Madrid (Portal Regional) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Comunidad de Madrid (Portal Regional) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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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="Comunidad de Madrid (Portal Regional) Analyst",
        goal="Access and analyze Comunidad de Madrid (Portal Regional) data via MCP.",
        backstory="Expert analyst with direct Comunidad de Madrid (Portal Regional) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Comunidad de Madrid (Portal Regional) 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 Comunidad de Madrid (Portal Regional). 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 Comunidad de Madrid (Portal Regional) MCP in CrewAI

They absolutely can. By sharing the MCP connection, your crew members pass findings back and forth to complete complex research projects.

Use the tool filter in your agent definition. This restricts the agent to only the specific functions required for its assigned task.

It does. You can connect using stdio, SSE, or Streamable HTTP depending on your local or production environment setup.

They are. Once you define the process, the agents execute the research and analysis loop until the goal is met.

All data accessed by your agents is kept within your local memory and execution environment. No third party ever sees the regional records your crew fetches.

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