How to Use the Comunidad de Madrid (Portal Regional) MCP in OpenAI Agents SDK

Q: How do I register the Comunidad de Madrid (Portal Regional) MCP Server in OpenAI Agents SDK?

Install the package using pip install openai-agents first. Set up the MCPServerStreamableHttp client with your Vinkius endpoint URL, and pass it to your Agent constructor in the mcpservers list. Enable cacheToolsList=True to speed up tool discovery during initialization.

Q: Can my OpenAI Agents SDK system search for specific topics like transport or health?

Yes, your agent uses searchdatasets to filter Madrid's portal by terms like 'transporte' or 'salud'. It returns matching dataset IDs that your agent can immediately query.

Q: How does the Comunidad de Madrid (Portal Regional) toolset handle high-volume queries in OpenAI Agents SDK?

The searchdatastore tool queries the SQL-like backend of the Madrid portal directly. To prevent timeouts, your agent should specify limit and offset parameters in its tool calls.

Q: What is the best way to inspect a dataset's structure before querying?

Have your agent call getdataset using the ID found via search. This returns the complete metadata, including field types, so the agent writes accurate datastore queries using the MCP protocol.

Query Comunidad de Madrid open data directly inside your OpenAI Agents SDK workflows with strict production guardrails.

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Connect Comunidad de Madrid (Portal Regional) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Comunidad de Madrid (Portal Regional) to OpenAI Agents SDK 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 OpenAI Agents SDK

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Query Madrid DataStore with OpenAI Agents SDK

`search_datastore` pulls real-time data from Madrid's public registers directly into your agent's execution context. You don't need manual CSV exports anymore; your agent pulls the exact rows directly. This MCP Server handles the connection details so your production agents can execute precise queries. Because the OpenAI Agents SDK supports strict runtime tracing, every query your agent makes to the Madrid datastore is logged and auditable in your dashboard.

Targeted Regional Dataset Discovery

`list_datasets` and `search_datasets` let your agent locate specific regional records, such as transportation schedules or healthcare metrics, using simple search queries. The agent scans the portal, finds the relevant dataset ID, and prepares to extract the underlying data. Once found, the agent calls `get_dataset` to read the structure and update its internal context. This MCP Server tool prevents your agent from guessing field names or hallucinating schema structures before running live queries.

Direct Resource File Extraction

`get_resource` extracts the actual files and endpoints associated with a Madrid open data registry. Your agent identifies the specific CSV or API resource, pulls its metadata, and prepares it for downstream processing. This tool ensures your agent operates on official, up-to-date regional files. By coupling this with OpenAI's agent handoffs, you can have one agent locate the resource and hand it to a specialized analysis agent.

Setup guide

Set up Comunidad de Madrid (Portal Regional) MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Comunidad de Madrid (Portal Regional) tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Comunidad de Madrid (Portal Regional) tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Comunidad de Madrid (Portal Regional) tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Comunidad de Madrid (Portal Regional) Agent",
            instructions="You have access to Comunidad de Madrid (Portal Regional) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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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 OpenAI Agents SDK

Install the package using `pip install openai-agents` first. Set up the `MCPServerStreamableHttp` client with your Vinkius endpoint URL, and pass it to your Agent constructor in the `mcp_servers` list. Enable `cacheToolsList=True` to speed up tool discovery during initialization.

Yes, your agent uses `search_datasets` to filter Madrid's portal by terms like 'transporte' or 'salud'. It returns matching dataset IDs that your agent can immediately query.

The `search_datastore` tool queries the SQL-like backend of the Madrid portal directly. To prevent timeouts, your agent should specify limit and offset parameters in its tool calls.

Have your agent call `get_dataset` using the ID found via search. This returns the complete metadata, including field types, so the agent writes accurate datastore queries using the MCP protocol.

This MCP Server only accesses public regional open data, meaning no classified or personal citizen information is ever exposed. Your Vinkius connection runs in a secure sandbox, preventing external data leaks while your agent reads public datasets.

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