How to Use the CDC WONDER (Epidemiologic Data) MCP in Google ADK

Q: How do I configure CDC WONDER (Epidemiologic Data) with Google ADK?

Install google-adk and create an McpToolset using StreamableHttpServerParameters with your Vinkius URL. Assign this MCP toolset to the tools array when initializing your LlmAgent.

Q: Can I restrict the CDC WONDER (Epidemiologic Data) tools my Google ADK agent sees?

Yes. You can apply the toolnames filter when setting up the toolset. This ensures your agent only has access to the specific operations you approve.

Connect Gemini to public health datasets. Google ADK agents pull and analyze CDC WONDER records across massive token contexts.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect CDC WONDER (Epidemiologic Data) MCP to Google ADK

Create your Vinkius account to connect CDC WONDER (Epidemiologic Data) to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup CDC WONDER (Epidemiologic Data) with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Feed epidemiologic data into Gemini contexts

Analyzing decades of mortality trends requires huge context windows. Google ADK lets your enterprise agents pull raw public health data straight into Gemini using the `query_wonder_database` tool via the MCP standard. You initialize the connection using `McpToolset` and pass it to your LlmAgent. The agent translates your natural language questions into the strict JSON parameter structures the CDC requires, handling all the obscure B_ and M_ prefixes automatically.

Bridge CDC WONDER MCP Server with BigQuery

Enterprise health research usually means combining public statistics with internal datasets. Your Google ADK agent fetches external vaccine adverse event data while simultaneously querying your private BigQuery tables. The agent acts as the routing layer between the public CDC endpoint and Google Cloud infrastructure. It extracts the exact demographic cuts you need via `query_wonder_database` and formats them for immediate Vertex AI analysis.

Process massive public health payloads

CDC WONDER returns dense, heavily structured demographic breakdowns. Gemini's massive token context window absorbs these huge payloads without losing track of the original research question. Ask the agent to compare state-level birth rates over a ten-year period. It fires off multiple targeted queries, ingests the resulting data blocks, and synthesizes a complete epidemiological report in one pass.

Setup guide

Set up CDC WONDER (Epidemiologic Data) 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 CDC WONDER (Epidemiologic Data) 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="CDC WONDER (Epidemiologic Data)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to CDC WONDER (Epidemiologic Data) 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 CDC WONDER. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect CDC WONDER (Epidemiologic Data) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about CDC WONDER (Epidemiologic Data) MCP in Google ADK

Install `google-adk` and create an `McpToolset` using `StreamableHttpServerParameters` with your Vinkius URL. Assign this MCP toolset to the `tools` array when initializing your `LlmAgent`.

The tool accepts any standard CDC database ID. Your agent can query D76 for mortality, or other specific codes for births and vaccine adverse events, provided it formats the JSON parameters correctly.

Yes. You can apply the `tool_names` filter when setting up the toolset. This ensures your agent only has access to the specific operations you approve.

Gemini reads the MCP schema provided by Vinkius and maps your plain English requests to the correct technical fields. It builds the required JSON object with the right V_, F_, and O_ prefixes without human intervention.

Your request parameters for mortality or birth statistics are processed securely through an MCP server running in a zero-trust V8 sandbox. Vinkius drops the ephemeral instance immediately after the data returns, leaving no trace of your specific geographic targets.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript