How to Use the Data.gov Catalog MCP in OpenAI Agents SDK

Q: How do I connect the Data.gov Catalog MCP Server to the OpenAI Agents SDK?

Install openai-agents via pip. Initialize MCPServerStreamableHttp with your Vinkius URL and pass it to the mcpservers array in your Agent constructor. The SDK handles tool discovery automatically.

Q: Can the OpenAI Agents SDK cache Data.gov Catalog responses?

Yes, you can optimize performance by setting cacheToolsList=True. This prevents the agent from re-fetching the tool definitions every time it initializes.

Q: Do I need to manually map the location tools?

No. The agent reads the tool descriptions for searchlocations and getlocationgeometry on boot. It figures out the required parameters without any manual routing on your end.

Build production-ready agents with the OpenAI Agents SDK that query US government datasets with built-in safety guardrails.

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Connect Data.gov Catalog MCP to OpenAI Agents SDK

Create your Vinkius account to connect Data.gov Catalog 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 Data.gov Catalog with OpenAI Agents SDK

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Perplexity

Spatial Search with OpenAI Agents SDK

Your agent needs federal data bounded by specific geographic coordinates. Calling `search_locations` auto-completes the location string and passes the exact ID directly to `get_location_geometry`. The system grabs the GeoJSON boundary without you writing any custom parsing logic. This setup thrives under the OpenAI guardrails system. If the agent tries to pull a massive dataset via `search_datasets` that violates your token limits, the SDK intercepts the call before execution. You get federal records routed safely into your processing pipeline.

Trace Data Provenance

Government datasets often have complex origins. When your agent runs `get_harvest_record`, it pulls the exact metadata showing how a specific file entered the federal catalog. Handoffs make this process incredibly powerful. One specialized agent can execute `get_harvest_record_raw` to inspect the unmodified payload, while a separate compliance agent reviews the DCAT-US format using `get_harvest_record_transformed`. Everything gets logged straight to your OpenAI dashboard for full visibility.

Map Federal Publishers via MCP Server

Finding out which agency published what requires digging through thousands of records. Executing `get_organizations` hands your agent the complete directory of publishing entities in one shot. Pair that with `get_keywords` to see exactly how agencies tag their datasets. The agent can auto-discover these MCP tools on startup, mapping out the entire federal data structure before running a single user query.

Setup guide

Set up Data.gov Catalog 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 Data.gov Catalog tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Data.gov Catalog tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Data.gov Catalog 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="Data.gov Catalog Agent",
            instructions="You have access to Data.gov Catalog 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 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 Catalog MCP in OpenAI Agents SDK

Install `openai-agents` via pip. Initialize `MCPServerStreamableHttp` with your Vinkius URL and pass it to the `mcp_servers` array in your Agent constructor. The SDK handles tool discovery automatically.

Yes, you can optimize performance by setting `cacheToolsList=True`. This prevents the agent from re-fetching the tool definitions every time it initializes.

The built-in tracing catches the failure and logs it to your dashboard. You can configure your agent to retry the `search_datasets` call or hand off the error to a fallback agent.

No. The agent reads the tool descriptions for `search_locations` and `get_location_geometry` on boot. It figures out the required parameters without any manual routing on your end.

It only reads public federal metadata, GeoJSON boundaries, and harvest records. Vinkius runs the connection inside a V8 isolate sandbox, destroying the environment after your token expires so no payload data leaks between sessions.

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