How to Use the DingConnect MCP in Google ADK

Q: How do I initialize the DingConnect tools within my Google ADK setup?

Use McpToolset with your HTTP server parameters and pass it to LlmAgent. Your Gemini model will immediately know how to call listmobileoperators via the MCP interface.

Q: How does Google ADK handle Gemini's long context with DingConnect?

Your agent can pull large datasets from listavailabletopupproducts or listtransactionhistory and analyze them inside Gemini's massive context window without running out of memory.

Q: How does the agent find specific mobile plans?

The agent runs searchtopupproducts to match user keywords against active data packages and pricing structures.

Q: Where does my DingConnect API credential and mobile operator data go?

All credentials and operator lists fetched via listmobileoperators are processed inside isolated MCP environments. Your sensitive keys never touch external public logs.

Connect your Google ADK enterprise agents to global mobile operators and manage balances directly from Gemini.

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Setup DingConnect with Google ADK

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Query global telcos via the DingConnect MCP Server

Give your Gemini models the ability to scan international mobile markets. Your agent uses `list_supported_countries` to see where services are active, then narrows it down with `list_mobile_operators` to find specific local carriers. This setup lets you process complex telco queries without building custom API wrappers. The agent handles the lookup steps dynamically during conversation.

Monitor live API balances and metadata

Keep your Google Cloud workflows informed about your financial limits. The agent calls `get_account_credit_balance` to check your current funding status before triggering high-volume top-up routines using the MCP toolset. It can also run `get_api_account_metadata` to verify account configurations. This ensures your agent works within your exact API limits and prevents over-allocation of funds.

Analyze market performance and transaction history

Combine long-context reasoning with actual transaction data. Your agent pulls historical records using `list_transaction_history` to identify trends or resolve transfer disputes. It can also run `list_top_volume_countries` to spot high-performance regions. This gives your agent the data it needs to recommend optimal routing strategies through the MCP Server.

Setup guide

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

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Common questions about DingConnect MCP in Google ADK

Use `McpToolset` with your HTTP server parameters and pass it to `LlmAgent`. Your Gemini model will immediately know how to call `list_mobile_operators` via the MCP interface.

Yes. You can apply a tool name filter when defining your toolset, limiting the agent to specific actions like `check_mobile_service_status` while hiding balance tools.

Your agent can pull large datasets from `list_available_topup_products` or `list_transaction_history` and analyze them inside Gemini's massive context window without running out of memory.

The agent runs `search_topup_products` to match user keywords against active data packages and pricing structures.

All credentials and operator lists fetched via `list_mobile_operators` are processed inside isolated MCP environments. Your sensitive keys never touch external public logs.

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