How to Use the Kavkom MCP in Google ADK

Q: Can I filter which Kavkom tools the Google ADK agent uses?

Yes, pass a toolnames filter to your toolset configuration. This allows you to expose only listcalls or sendsmsmessage if your agent does not need full account access.

Q: How does this handle large call history lists in Google ADK?

The server returns paginated data via listcalls. Your agent can iterate through these results, allowing you to process massive call logs without hitting memory limits.

Connect your Google ADK enterprise agents to Kavkom for automated telephony and CRM operations.

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Connect Kavkom MCP to Google ADK

Create your Vinkius account to connect Kavkom 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 Kavkom with Google ADK

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Sync Kavkom tools with Google ADK

The McpToolset class bridges your Google infrastructure to Kavkom. It exposes `list_calls` and `list_crm_contacts` so your Gemini-powered agents can reason over your telephony data. Define a tool_names filter to restrict access to specific functions. This keeps your agent focused on the tasks that matter for your current workflow.

Process call data within your cloud stack

Use `get_call_details` to retrieve specific call logs and pipe them into BigQuery for analysis. Your agent acts as the bridge between raw telephony data and your cloud storage. This setup allows you to run complex reasoning over 1M+ tokens of call history. You get deep insights without manually exporting CSV files.

Send SMS and manage team availability

Trigger `send_sms_message` to automate notifications based on triggers in your Vertex AI environment. The agent handles the delivery while you monitor performance in the Google Cloud console. Call `list_team_members` to ensure your agent routes requests to active users only. It keeps your operations aligned with the current office status.

Setup guide

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

Install the server and initialize an McpToolset with your endpoint URL. Pass this toolset into your LlmAgent constructor to give it immediate access to all Kavkom functions.

Yes, the server supports both Stdio and HTTP transports. You can choose the connection method that best fits your Google Cloud deployment architecture.

Absolutely. The Kavkom server uses an ephemeral sandbox for all requests. Your CRM contacts and call logs never persist beyond the session execution.

Yes, pass a tool_names filter to your toolset configuration. This allows you to expose only `list_calls` or `send_sms_message` if your agent does not need full account access.

The server returns paginated data via `list_calls`. Your agent can iterate through these results, allowing you to process massive call logs without hitting memory limits.

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