How to Use the Aragón Open Data MCP in AutoGen

Q: How do I add Aragón Open Data to AutoGen?

Initialize StreamableHttpServerParams with your Vinkius URL. The McpToolAdapter automatically converts the tools for your AssistantAgent.

Give your AutoGen agents access to the Aragón government open data catalog.

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Connect Aragón Open Data MCP to AutoGen

Create your Vinkius account to connect Aragón Open Data to AutoGen 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 Aragón Open Data with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Debate public data sources

The `search_datasets` tool lets your MCP-enabled researcher agent hunt for relevant government statistics. A separate analyst agent reviews the findings and argues whether the source fits the user's requirements. This multi-agent setup ensures higher accuracy. If the first agent picks a poorly documented package, the second agent demands they find a better one before presenting the final report.

Analyze schemas with AutoGen

Calling `show_columns` exposes the structural metadata of a specific view. A data-engineer agent reads this schema and writes a Python script to process the fields. Meanwhile, a QA agent reviews the proposed script against the column definitions. They negotiate the data types and handling logic until both agree the code will run without errors.

Cross-reference government publishers

Running `get_organization` pulls the exact details of the department that published a dataset. Your agents use this context to weigh the authority and reliability of the information. Teams might combine this with `most_downloaded_datasets` to see what the public actually cares about. The resulting conversation yields a highly contextualized briefing on regional priorities.

Setup guide

Set up Aragón Open Data MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Aragón Open Data tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Aragón Open Data_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Aragón Open Data data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Aragón Open Data_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Aragón Open Data data")
    print(result.messages[-1].content)

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 Aragón Open Data. 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 Aragón Open Data MCP in AutoGen

Initialize `StreamableHttpServerParams` with your Vinkius URL. The `McpToolAdapter` automatically converts the tools for your `AssistantAgent`.

Your coder agent drafts the syntax and attempts to execute it. If the endpoint returns an error, the agent reads the output and corrects the query on the fly.

Yes, the fetched records enter the shared conversation context. Every agent in the chat can read the downloaded rows and base their arguments on them.

The default preview limit is 1000 rows per call. Agents analyze this sample to understand the dataset's contents before deciding on next steps.

Your MCP conversation history and data queries run through a secure, ephemeral sandbox. We never log the specific government records your agents pull or the analysis they generate.

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