How to Use the ZoomInfo MCP in Google ADK

Q: What if I want to get news articles using ZoomInfo?

You simply call getcompanynews. This pulls relevant, current information directly into your agent's context. It’s a straightforward function that adds immediate depth to any profile.

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Connect ZoomInfo MCP to Google ADK

Create your Vinkius account to connect ZoomInfo 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.

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Setup ZoomInfo with Google ADK

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Search B2B Data With ZoomInfo MCP Server

The `search_companies` tool provides immediate access to company records for your agents. Since you're running this on Google Cloud, these results flow naturally into BigQuery for massive analysis. Additionally, the agent can search contacts using `search_contacts`. This keeps all of your lead data within your existing GCP infrastructure.

Enrich Records Using ZoomInfo MCP Server

When an agent finds a partial record, it calls `enrich_company` or `enrich_contact`. The tool returns the necessary depth—things like employee size or industry verticals—which your Gemini models can then reason over. This is critical when working with 1M+ tokens of context; you don't want vague data points slowing down complex reasoning.

Analyze Intent Signals With ZoomInfo MCP Server

You use `search_intent` to see what topics companies are researching. Your agent pulls these signals and can immediately cross-reference them with company details using the raw data. This means you're not just getting a list; you’re building a narrative that lives entirely within your Google Cloud workspace.

Setup guide

Set up ZoomInfo 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 ZoomInfo 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="ZoomInfo_agent",
    model="gemini-2.0-flash",
    instruction="You have access to ZoomInfo tools via MCP.",
    tools=mcp_tools,
)

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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 ZoomInfo. 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 ZoomInfo MCP in Google ADK

You set up the MCP Toolset pointing to the server URL. Your LlmAgent then treats this tool like any other data source, allowing your long-context Gemini model to process it natively.

Absolutely. The native integration with BigQuery means you're designed for massive scale. You can hold vast amounts of data and perform complex reasoning on it without hitting limits.

The server provides access to Company records, Contact records, and Intent Signals. Your agents can use these distinct data streams for multi-faceted analysis in BigQuery.

You simply call `get_company_news`. This pulls relevant, current information directly into your agent's context. It’s a straightforward function that adds immediate depth to any profile.

The server touches Company records and Contact records. These structured types are ready for high-volume processing in your Google Cloud environment.

Use it with your favorite AI tools

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