How to Use the Daktela MCP in Google ADK

Q: How do I configure Daktela tools inside Google ADK?

Initialize McpToolset with your Vinkius Daktela HTTP server parameters. Pass this MCP toolset directly into your Google ADK LlmAgent tools array to expose Daktela's API capabilities.

Q: Can Google ADK agents filter which Daktela tools are exposed?

Yes, you can use the optional toolnames filter in the toolset configuration inside Google ADK. This restricts your Gemini agent to specific Daktela tools like getticket or listcontacts.

Q: How does Google ADK handle Daktela contact center queues?

Your Google ADK agent runs listqueues to inspect Daktela queue status. It can combine this Daktela data with Vertex AI models to predict queue bottlenecks and alert team leads.

Q: Where does my Daktela CRM contact data go during processing?

Your Daktela CRM contacts accessed via listcontacts and createcontact flow through ephemeral, zero-trust V8 isolates. No Daktela contact records are written to disk or used to train Google ADK foundation models.

Analyze Daktela call logs and manage CRM records with Google ADK agents using Gemini long-context reasoning.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Daktela MCP to Google ADK

Create your Vinkius account to connect Daktela 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 Daktela with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Feed Daktela call logs into Google ADK pipelines

The `list_call_history` tool feeds raw Daktela contact center logs directly into your Google ADK agent's Gemini context window. This lets your Google ADK agent analyze hours of Daktela customer interactions without hitting token limits. Your Google ADK agent cross-references these logs with `list_activities` to map Daktela phone calls to specific CRM events. You can then export these structured Daktela insights directly into BigQuery via your Google ADK pipeline.

Sync Gemini reasoning with this Daktela MCP Server

The `create_ticket` tool allows your Google ADK agent to open Daktela support cases based on emails processed in Vertex AI. Your Google ADK agent reads the incoming message, summarizes the issue, and writes the Daktela ticket. You use `list_queues` to find the right Daktela department for the ticket. The Google ADK agent assigns the task to the Daktela queue with the lowest wait time, keeping your support operations fast.

Manage corporate accounts inside Google Cloud agents

The `list_accounts` tool exposes your Daktela CRM accounts to your Google ADK workflow. Your Google ADK agent queries this list to match incoming customer phone numbers with Daktela enterprise account records. It updates Daktela records using `create_contact` when new stakeholders join an account. This keeps your Daktela sales and support data synchronized without manual data entry in Google ADK, using native MCP protocols.

Setup guide

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

Initialize `McpToolset` with your Vinkius Daktela HTTP server parameters. Pass this MCP toolset directly into your Google ADK `LlmAgent` tools array to expose Daktela's API capabilities.

Yes, you can use the optional `tool_names` filter in the toolset configuration inside Google ADK. This restricts your Gemini agent to specific Daktela tools like `get_ticket` or `list_contacts`.

Your Google ADK agent runs `list_queues` to inspect Daktela queue status. It can combine this Daktela data with Vertex AI models to predict queue bottlenecks and alert team leads.

Yes, the Daktela integration supports both Stdio and HTTP transports. For cloud-hosted Google ADK agents, the Streamable HTTP transport is the recommended choice.

Your Daktela CRM contacts accessed via `list_contacts` and `create_contact` flow through ephemeral, zero-trust V8 isolates. No Daktela contact records are written to disk or used to train Google ADK foundation models.

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