How to Use the Clientify MCP in Google ADK

Q: Will Google ADK restrict which Clientify tools I use?

You can use a toolnames filter to limit exposure. This prevents the agent from accessing sensitive CRM operations if you only need it to read data.

Integrate Clientify into your Google ADK agents. Build high-context sales automation on the Gemini infrastructure.

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Connect Clientify MCP to Google ADK

Create your Vinkius account to connect Clientify 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 Clientify with Google ADK

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Google ADK tools for Clientify CRM

Access your CRM data using `get_contact` to pull specific records for your agent. Gemini models use this context to inform follow-up strategies for specific leads. Run `list_contacts` to search across your entire database. The agent processes these lists to find patterns in lead behavior without manual intervention.

Pipeline visibility with Google ADK

Fetch deal information using `list_deals` to feed your agent's reasoning process. It understands the status of every prospect currently in your pipeline. Query `list_pipelines` to understand your current sales structure. Your agent identifies gaps in your process by analyzing the output from this tool.

Automated activity logging in Google ADK

Create new tasks using `create_activity` whenever your agent finishes a lead analysis. This saves you from switching tabs to log your next steps. Monitor your team's workload with `list_users`. Your agent checks who is available to assign new tasks to, ensuring your team stays productive.

Setup guide

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

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Common questions about Clientify MCP in Google ADK

Use the McpToolset class in your Python script. Point it to the server URL provided by Vinkius and pass it into your LlmAgent instance.

You can use a tool_names filter to limit exposure. This prevents the agent from accessing sensitive CRM operations if you only need it to read data.

Gemini models handle massive context windows, making them ideal for parsing large lists of CRM data. You can feed your entire contact database into the context for deep analysis.

The server uses authenticated tokens for every request. Vinkius manages the connection, ensuring your CRM credentials stay isolated from your agent code.

Your CRM records are transmitted over encrypted tunnels only when the agent invokes a tool. Vinkius wipes the memory buffer immediately after the transaction completes.

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