How to Use the Kylas MCP in Google ADK

Q: How do I configure this MCP Server with Google ADK?

Install the package and instantiate McpToolset using your Vinkius HTTP endpoint. Pass that toolset directly to your LlmAgent constructor.

Q: Can my Gemini agent read every Kylas lead at once?

Yes. You use listleads to pull the records. Gemini's million-token context window easily absorbs the entire Indian SMB pipeline for complex reasoning tasks.

Connect Kylas to Google ADK and let Gemini agents manage your sales pipeline alongside BigQuery.

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Connect Kylas MCP to Google ADK

Create your Vinkius account to connect Kylas 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 Kylas with Google ADK

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Sync Kylas deals via MCP Server

The `list_deals` and `get_lead` tools push your active sales data straight into Gemini's massive context window. Your agent pulls hundreds of deal records at once and cross-references them against your existing BigQuery datasets. Google ADK handles the routing. You set up the toolset, and your Gemini model decides when to fetch specific SMB prospect details to answer enterprise queries.

Generate CRM contacts automatically

The `create_contact` and `create_lead` tools allow your Vertex AI agents to write new entries into the CRM. You feed a raw JSON string into the lead tool, and the system registers the prospect. This replaces manual data entry for your sales team. Your agent processes incoming WhatsApp logs stored in Cloud Storage, extracts the relevant phone numbers, and generates the CRM records instantly.

Audit tasks with Google ADK

The `list_tasks` and `list_contacts` tools give your Google Cloud application total visibility into sales rep activity through this MCP Server. The agent fetches the daily task list and compares it against actual contact creation volume. You filter which operations the agent can see using the `tool_names` parameter. If you only want the agent reading tasks and not creating leads, you restrict the array at the framework level.

Setup guide

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

Install the package and instantiate `McpToolset` using your Vinkius HTTP endpoint. Pass that toolset directly to your `LlmAgent` constructor.

Yes. You use `list_leads` to pull the records. Gemini's million-token context window easily absorbs the entire Indian SMB pipeline for complex reasoning tasks.

Use the optional tool names filter when setting up the toolset. This prevents your agent from accidentally calling `create_lead` when it should only be analyzing data.

It works natively. The Vinkius endpoint acts as a standard HTTP transport layer. Your Vertex architecture just sees another accessible API.

Your customer phone numbers and deal values never touch a persistent disk. Vinkius processes every request through a zero-trust architecture. We authenticate via a single token and discard the state immediately.

Use it with your favorite AI tools

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