How to Use the Apollo.io MCP in Google ADK

Q: How do I connect the Apollo.io MCP Server to my Google ADK agent?

Instantiate McpToolset with your Vinkius HTTP server parameters and pass it to your LlmAgent tools list. The Gemini model automatically discovers and executes the tools as needed.

Q: Can I restrict which Apollo.io tools my Google ADK agent can access?

Yes, you can pass a list of allowed tool names to your McpToolset parameters to restrict access. This prevents an agent from calling addtosequence while allowing it to run searches.

Q: Does Google ADK support real-time credit tracking for Apollo.io?

Your agent can call getcreditinfo at the start of any pipeline execution to check your remaining balance. This lets you build conditional logic that pauses heavy enrichment tasks if your monthly credits are low.

Q: How does the Google ADK MCP toolset handle large payloads from Apollo.io search tools?

The toolset passes the raw JSON from searchpeople directly into the Gemini context window. Thanks to the model's million-token capacity, you can analyze hundreds of prospect records in a single prompt.

Feed Apollo.io prospecting data directly into Gemini long-context models using Google ADK to build enterprise outbound pipelines.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Apollo.io MCP to Google ADK

Create your Vinkius account to connect Apollo.io 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 Apollo.io with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Long-context lead matching via Google ADK

`search_companies` queries target organizations and feeds raw firmographic data directly into Gemini's massive 1M-token context window. Google ADK lets your agent process thousands of company profiles simultaneously, matching prospects against your BigQuery customer tables in a single pass. Instead of running slow, iterative queries, your agent analyzes entire market segments at once. The native Google Cloud integration allows the agent to cross-reference Apollo data with internal warehouse records without moving data outside your secure perimeter.

Scale profile enrichment with this MCP Server

`enrich_person_data` pulls complete contact profiles, including direct dials and email histories, directly into your Vertex AI pipelines. Google ADK manages the execution flow, allowing your Gemini-powered agent to evaluate lead quality using complex reasoning chains. Because the framework is built for enterprise scale, you can run parallel enrichment jobs across thousands of records. This MCP Server uses `get_api_health` to verify connection status before starting massive batch jobs, ensuring zero dropped requests.

Automate sequences from Google ADK

`add_to_sequence` injects verified leads into active sales campaigns directly from your Python runtime. Your agent lists your current campaigns with `list_sales_sequences` and selects the optimal path based on intent signals analyzed by Vertex AI. This eliminates the need for complex glue code between your data warehouse and your sales engagement platform. The agent verifies sender availability via `list_connected_emails` and schedules the outreach, tracking everything in your cloud logs.

Setup guide

Set up Apollo.io 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 Apollo.io 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="Apollo.io_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Apollo.io 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 Apollo.io. 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 Apollo.io 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 Apollo.io MCP in Google ADK

Instantiate `McpToolset` with your Vinkius HTTP server parameters and pass it to your `LlmAgent` tools list. The Gemini model automatically discovers and executes the tools as needed.

Yes, you can pass a list of allowed tool names to your `McpToolset` parameters to restrict access. This prevents an agent from calling `add_to_sequence` while allowing it to run searches.

Your agent can call `get_credit_info` at the start of any pipeline execution to check your remaining balance. This lets you build conditional logic that pauses heavy enrichment tasks if your monthly credits are low.

The toolset passes the raw JSON from `search_people` directly into the Gemini context window. Thanks to the model's million-token capacity, you can analyze hundreds of prospect records in a single prompt.

All communication between Gemini, Vinkius, and Apollo.io is encrypted in transit. Your prospect lists, email addresses, and direct dials are processed entirely within your Google Cloud project boundary.

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