How to Use the Dixa MCP in Google ADK

Q: How do I register the Dixa MCP Server within my Google ADK agent?

Initialize McpToolset with your Vinkius HTTP URL in Python. Pass that toolset directly to your LlmAgent constructor to give your Gemini models instant access to all ten support tools.

Q: Can I limit which Dixa tools the Google ADK agent can access?

Yes. You can pass a toolnames filter to your McpToolset to expose only specific tools like listopensupporttickets while hiding administrative functions.

Q: How does Gemini use Dixa data for long-context reasoning in the Google ADK?

Your Google ADK agent pulls raw conversation details via getconversationdetails and injects them into the Gemini prompt. The model uses its large token capacity to analyze complex support histories without losing context.

Q: How do I inspect active support queues?

Your agent executes listservicequeues to get a real-time snapshot of pending workloads. This helps your Python pipeline balance traffic across different communication channels.

Connect Gemini's million-token context to Dixa support queues using the Google ADK.

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Connect Dixa MCP to Google ADK

Create your Vinkius account to connect Dixa 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 Dixa with Google ADK

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Link Dixa customer history to Google ADK pipelines

`list_customer_conversations` retrieves complete customer histories and feeds them directly into Gemini's massive context window. Your Google ADK agent analyzes years of support logs in a single turn. This MCP Server setup lets your agent run `get_conversation_details` to extract deep insights from specific threads. You can then cross-reference this support data with your enterprise BigQuery warehouse using native Google Cloud tools.

Track agent capacity across support teams

`list_support_teams` provides a clear map of your organization's human resources directly to your Gemini agent. The agent uses this list to understand team structures before routing complex tickets. By calling `quick_agent_presence_audit`, your Python code checks who is active right now. This prevents the agent from assigning urgent tasks to teammates who are out of the office or on break.

Surface open tickets for immediate routing

`list_open_support_tickets` identifies unassigned conversations that need urgent attention. Your Google ADK agent monitors this endpoint to keep your queue empty. When a ticket matches a specific pattern, the agent runs `search_conversations_by_subject` to find historical resolutions. This allows the agent to draft accurate replies based on proven fixes.

Setup guide

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

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Common questions about Dixa MCP in Google ADK

Initialize `McpToolset` with your Vinkius HTTP URL in Python. Pass that toolset directly to your `LlmAgent` constructor to give your Gemini models instant access to all ten support tools.

Yes. You can pass a `tool_names` filter to your `McpToolset` to expose only specific tools like `list_open_support_tickets` while hiding administrative functions.

Your Google ADK agent pulls raw conversation details via `get_conversation_details` and injects them into the Gemini prompt. The model uses its large token capacity to analyze complex support histories without losing context.

Your agent executes `list_service_queues` to get a real-time snapshot of pending workloads. This helps your Python pipeline balance traffic across different communication channels.

Your customer conversations and agent profiles remain inside your secure Dixa account and are only fetched on demand. The Google ADK passes this data through encrypted channels directly to your Vertex AI instance, leaving no persistent footprint on Vinkius.

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