How to Use the U.S. Census Full — Complete Demographic & Economic Intelligence MCP in Google ADK

Q: Does U.S. Census Full — Complete Demographic & Economic Intelligence support multi-geography searches with Google ADK?

The querycensus tool allows you to combine variables and geographies—you can query by state, county, or place simultaneously.

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Connect U.S. Census Full — Complete Demographic & Economic Intelligence MCP to Google ADK

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Setup U.S. Census Full — Complete Demographic & Economic Intelligence with Google ADK

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Use the Google ADK to query full state intelligence

The `get_state_profile` tool pulls a complete socioeconomic profile for an entire state in one go. This single call gives you population, housing data, income stats, and demographics—everything needed for high-level analysis. Your Gemini model can hold all that context using Google ADK's long-context reasoning, making it easy to analyze multiple facets of a single market.

Get population metrics via Google ADK

Need total populations? The `get_population_by_state` tool provides the total count and median age for all 50 states plus DC. If you want to narrow it down, `get_population_by_county` uses state FIPS codes for precise targeting. This data is perfect for building regional models in BigQuery.

Run custom Census queries using the MCP Server

The universal `query_census` tool lets you specify any variable and geography needed. This means your agent isn't limited to pre-packaged calls; it can grab specific datasets like educational attainment (`get_education_by_state`) or housing values. This flexibility is key when running enterprise agents on Google Cloud, allowing the model to adapt to unique data requirements.

Setup guide

Set up U.S. Census Full — Complete Demographic & Economic Intelligence MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with U.S. Census Full — Complete Demographic & Economic Intelligence tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="U.S. Census Full — Complete Demographic & Economic Intelligence_agent",
    model="gemini-2.0-flash",
    instruction="You have access to U.S. Census Full — Complete Demographic & Economic Intelligence tools via MCP.",
    tools=mcp_tools,
)

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 U.S. Census Bureau. 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 U.S. Census Full — Complete Demographic & Economic Intelligence MCP in Google ADK

The MCP Server acts as an external toolset that your Gemini model can call natively. It lets your agent perform data retrieval and calculation before reasoning, keeping the workflow contained within Google Cloud.

Yes. The long context window of Gemini models using Google ADK supports comparing data across multiple states—for instance, comparing housing vacancy rates (`get_housing_by_state`) between California and Florida.

It provides median household income for all counties, which helps identify economic disparities within a state, or compare poverty rates across different regions using `get_income_by_county`.

The `query_census` tool allows you to combine variables and geographies—you can query by state, county, or place simultaneously.

The server touches on real estate values, including both rent and ownership rates, provided through tools like `get_housing_by_county`.

Use it with your favorite AI tools

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