How to Use the Google Civic Information MCP in AutoGen
Build multi-agent debates in AutoGen to verify voter registrations and locate polling places with zero friction.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Google Civic Information MCP to AutoGen
Create your Vinkius account to connect Google Civic Information 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.
Verify Public Officials with AutoGen Teams
The `get_representatives_by_address` tool outputs the complete roster of elected officials for any address. In AutoGen, one agent can pull this data via our MCP Server while a second agent verifies the contact details against local government directories. This multi-agent setup prevents errors by forcing agents to cross-check their outputs. The conversation continues until both agents agree that the representative mapping is correct and complete.
Coordinate Voter Information Retrieval
The `get_voter_information` tool provides polling site locations and ballot information based on address inputs. An AutoGen coordinator agent assigns this MCP tool to a data-fetching agent, then passes the output to a compliance agent. The compliance agent checks the active elections returned by `get_google_civic_elections` to confirm the date matches. This team-based approach ensures users never receive outdated polling information.
Resolve Electoral Boundaries with AutoGen
The `search_civic_divisions` tool resolves municipal boundaries into standard OCD-IDs. When a location query is ambiguous, your AutoGen agents debate the correct jurisdiction before querying representative data. The system runs `check_api_status` at the start of the session to ensure the endpoint is active. If the API is down, the supervisor agent pauses the workflow and alerts the user instead of wasting API calls.
Set up Google Civic Information 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Google Civic Information tools and returns structured results.
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="Google Civic Information_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Google Civic Information data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Google Civic Information_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Google Civic Information data")
print(result.messages[-1].content) 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 AutoGen
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