How to Use the Data.gov MCP in AutoGen

Multi-agent debate powered by Data.gov and AutoGen. Let your agents cross-examine federal records to reach a consensus.

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Connect Data.gov MCP to AutoGen

Create your Vinkius account to connect Data.gov 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 Data.gov with AutoGen

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Perplexity

Debate federal data points with AutoGen agents

Assign one agent to fetch data with `search_datasets` while another challenges the findings. They negotiate until they agree on the most relevant dataset. This workflow forces your agents to verify facts against the source. It prevents the common errors found in single-agent setups.

Coordinate complex research with Data.gov tools

Use `get_organization_datasets` to assign specific research tasks to different agents. One agent gathers the stats, the other summarizes the findings for the user. Your AutoGen system manages the flow of information between these specialized roles. It makes handling massive federal repositories much easier.

Automate consensus on government data analysis

Configure your agents to use `get_status` for auditing the state of the Data.gov catalog. They discuss the findings to ensure they are working with the latest information. This multi-agent approach handles the nuance of government data. They don't just act, they deliberate before delivering a final result.

Setup guide

Set up Data.gov 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 Data.gov 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="Data.gov_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Data.gov 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="Data.gov_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Data.gov 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 Data.gov. 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 Data.gov MCP in AutoGen

You give your agents access to the tools, and they perform the calls as part of their conversation. When one agent retrieves a dataset, the other reviews it for accuracy.

Yes, the server fits right into your agent group chat. The agents call the tools, receive the JSON output, and incorporate that data into their next reply.

You control the tool list in the agent constructor. You can limit your agents to only read-only search tools to maintain a secure research environment.

The agents see the error message in the chat history. They can then decide to try a different query or rephrase their request based on that feedback.

All sessions are ephemeral and managed in a V8 sandbox. Your specific research queries and the resulting federal data are cleared once your agent conversation ends.

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