How to Use the Platform.ly MCP in Google ADK

Q: Can Google ADK agents filter which Platform.ly tools are available?

Yes. You can provide a toolnames filter to the toolset. This restricts the agent to only the specific CRM actions you choose to expose.

Integrate Platform.ly with your Google ADK agents to sync CRM data with your Vertex AI and BigQuery infrastructure.

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Connect Platform.ly MCP to Google ADK

Create your Vinkius account to connect Platform.ly to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Platform.ly with Google ADK

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Google ADK agents accessing CRM data

Your agents can now query your CRM directly alongside your BigQuery datasets. Use `get_contact_details` to pull specific user history into your model's 1M+ token context window. This creates a unified view for your Gemini-powered agents. They process CRM records and cloud data simultaneously to generate accurate, context-aware responses.

Streamline operations with Google ADK

Trigger contact updates from your existing Google Cloud workflows. Your agent uses `update_existing_contact` to reflect changes observed in your infrastructure analytics. This keeps your lead data synced across your entire stack. You define the logic, and the agent executes the CRM updates as part of your standard cloud pipeline.

Manage marketing segments via MCP Server

Your agent analyzes your database to identify high-value segments. It then uses `list_project_segments` and `apply_tag_to_contact` to organize your leads for targeted outreach. This MCP Server provides the bridge between your marketing logic and your CRM. The agent handles the segmentation tasks automatically based on the data patterns it finds.

Setup guide

Set up Platform.ly 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 Platform.ly 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="Platform.ly_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Platform.ly 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 Platform.ly. 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

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Common questions about Platform.ly MCP in Google ADK

Use the McpToolset class with your server URL. Pass this toolset into your LlmAgent to give your model access to the full suite of CRM operations.

Yes. You can provide a tool_names filter to the toolset. This restricts the agent to only the specific CRM actions you choose to expose.

It does. You can combine CRM data with your BigQuery queries within the same agent reasoning cycle. This allows for deep analysis of your customer base.

The framework supports both Stdio and HTTP transports. For remote deployments, the HTTP transport provides a persistent connection to your CRM tools.

The server uses token-based authentication for every request. No data is stored in the agent; it is retrieved on-demand from your CRM instance.

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