How to Use the Google Civic Information MCP in OpenAI Agents SDK
Run safe, multi-agent political workflows with the Google Civic Information MCP Server directly in your OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Google Civic Information MCP to OpenAI Agents SDK
Create your Vinkius account to connect Google Civic Information 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.
Find representatives with OpenAI Agents SDK
The `get_representatives_by_address` tool resolves physical street addresses into structured political office profiles. Your agents parse the raw address inputs, map them to current elected officials, and return exact district boundaries without manual lookup tables. This setup lets you build multi-agent handoffs where one agent extracts addresses from user chats, and a specialized civic agent retrieves the official representative data. The built-in OpenAI guardrails validate these tools before running them, preventing execution errors.
Track upcoming elections and polling sites
The `get_voter_information` tool pulls verified polling locations and ballot details for any validated address and election ID. It provides the exact coordinates and operating hours of voting booths to keep your users informed. Combine this with `get_google_civic_elections` to fetch active national or local contests. Your agent handles the scheduling, runs the queries asynchronously, and outputs clean JSON payloads directly to your application frontend.
Verify API health and search divisions
The `check_api_status` tool monitors the uptime of the upstream Google services before running heavy queries. It prevents your agent from hanging or wasting tokens on dead endpoints when local government servers experience downtime. Use `search_civic_divisions` to match geographic queries to official Open Civic Data identifiers. This ensures your agents use standardized boundary keys, avoiding address parsing errors in rural or unstructured voting districts.
Set up Google Civic Information MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Google Civic Information tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Google Civic Information tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Google Civic Information tools and returns structured results. Copy the full example on the right to get started.
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="Google Civic Information Agent",
instructions="You have access to Google Civic Information tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Civic Information. 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 Google Civic Information MCP in OpenAI Agents SDK
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