Comunidad de Madrid (Portal Regional) MCP Server for CrewAIGive CrewAI instant access to 5 tools to Get Dataset, Get Resource, List Datasets, and more

Name: Comunidad de Madrid (Portal Regional)
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Connect your CrewAI agents to Comunidad de Madrid (Portal Regional) through Vinkius, pass the Edge URL in the `mcps` parameter and every Comunidad de Madrid (Portal Regional) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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The Comunidad de Madrid (Portal Regional) MCP Server for CrewAI is a standout in the Knowledge Management category — giving your AI agent 5 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Comunidad de Madrid (Portal Regional) Specialist",
    goal="Help users interact with Comunidad de Madrid (Portal Regional) effectively",
    backstory=(
        "You are an expert at leveraging Comunidad de Madrid (Portal Regional) tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Comunidad de Madrid (Portal Regional) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 5 available tools "
        "and what they can do."
    ),
)

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

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About Comunidad de Madrid (Portal Regional) MCP Server

Connect your AI agent to the Comunidad de Madrid Open Data Portal to access a wealth of public information directly through natural language. This MCP server provides a bridge to the regional CKAN-based repository, covering everything from transport and health to environment and economy.

When paired with CrewAI, Comunidad de Madrid (Portal Regional) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Comunidad de Madrid (Portal Regional) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Dataset Discovery — Search for specific datasets using keywords like 'transporte', 'salud', or 'medio ambiente' to find relevant public records.
Metadata Inspection — Retrieve full metadata for datasets, including tags, organizations, and update frequencies.
Resource Management — List and inspect individual files (resources) within a dataset, such as CSVs, JSONs, or PDFs.
Direct Data Querying — Use the DataStore integration to query the actual content of datasets directly, allowing for data analysis without manual downloads.
Portal Exploration — List all available dataset identifiers to understand the scope of available regional data.

The Comunidad de Madrid (Portal Regional) MCP Server exposes 5 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 5 Comunidad de Madrid (Portal Regional) tools available for CrewAI

When CrewAI connects to Comunidad de Madrid (Portal Regional) through Vinkius, your AI agent gets direct access to every tool listed below — spanning madrid, open-data, ckan, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get dataset on Comunidad de Madrid (Portal Regional)

Get full metadata for a specific dataset

get

Get resource on Comunidad de Madrid (Portal Regional)

Get metadata for a specific resource

list

List datasets on Comunidad de Madrid (Portal Regional)

List all dataset identifiers in the portal

Search datasets on Comunidad de Madrid (Portal Regional)

g., transporte, salud). Search for datasets matching specific criteria

Search datastore on Comunidad de Madrid (Portal Regional)

Query data directly from a resource in the DataStore

Connect Comunidad de Madrid (Portal Regional) to CrewAI via MCP

Follow these steps to wire Comunidad de Madrid (Portal Regional) into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 5 tools from Comunidad de Madrid (Portal Regional)

Why Use CrewAI with the Comunidad de Madrid (Portal Regional) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Comunidad de Madrid (Portal Regional) through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Comunidad de Madrid (Portal Regional) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Comunidad de Madrid (Portal Regional) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Comunidad de Madrid (Portal Regional) for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Comunidad de Madrid (Portal Regional), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Comunidad de Madrid (Portal Regional) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Comunidad de Madrid (Portal Regional) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Comunidad de Madrid (Portal Regional) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Comunidad de Madrid (Portal Regional) immediately.

"Search for datasets related to air quality in Madrid."

"List all dataset identifiers available in the portal."

"Get the metadata for the dataset 'calidad_aire_datos_dia'."

Troubleshooting Comunidad de Madrid (Portal Regional) MCP Server with CrewAI

Common issues when connecting Comunidad de Madrid (Portal Regional) to CrewAI through Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Comunidad de Madrid (Portal Regional) + CrewAI FAQ

Common questions about integrating Comunidad de Madrid (Portal Regional) MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.