How to Use the Asian Development Bank MCP in Google ADK

Q: How do I configure the Asian Development Bank MCP Server in Google ADK?

Create an McpToolset using StreamableHttpServerParameters and your Vinkius endpoint. Injecting this toolset into your LlmAgent initialization lets Gemini automatically understand the available functions.

Feed massive Asia-Pacific economic datasets into your Gemini models using the Google ADK.

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Connect Asian Development Bank MCP to Google ADK

Create your Vinkius account to connect Asian Development Bank 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 Asian Development Bank with Google ADK

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Analyze GDP trends with Gemini

Gross domestic product metrics for regions like PRC, JPN, and IND arrive via the `get_gdp_asia` tool. Gemini's massive context window can ingest decades of this historical data at once. Piping these results directly into BigQuery works perfectly for long-term storage. Enterprise agents read the ADB figures and join them against your internal corporate datasets.

Monitor regional inflation rates

Fetching consumer price inflation requires a quick call to `get_inflation_asia`. This gives your LlmAgent immediate access to pricing shifts in markets like KOR, INO, and THA. Passing the `McpToolset` to your agent exposes these capabilities natively. Framework translations convert the HTTP transport responses into a format Vertex AI understands without manual parsing.

Custom Asian Development Bank MCP Server queries

Complex macroeconomic analysis relies on `query_adb_indicators`. Constructing specific requests using dataflow IDs like ADB,EO_INF isolates inflation, while ADB,EO_BOP targets trade balances. Filtering exposed tools through the `tool_names` parameter keeps your agent focused. Restricting the model strictly to trade data makes sense when building specialized supply chain agents.

Setup guide

Set up Asian Development Bank 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 Asian Development Bank 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="Asian Development Bank_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Asian Development Bank tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

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Common questions about Asian Development Bank MCP in Google ADK

Create an `McpToolset` using `StreamableHttpServerParameters` and your Vinkius endpoint. Injecting this toolset into your `LlmAgent` initialization lets Gemini automatically understand the available functions.

They definitely can. Custom query tools accept multiple indicators joined by a plus sign. Agents pull NGDP_XDC and PCPI_PCH simultaneously without issue.

It works perfectly. Writing raw JSON straight into BigQuery tables happens right after the agent retrieves the metrics. Data science teams then run SQL over the fresh numbers.

Specific inflation functions support PRC, JPN, IND, KOR, INO, THA, VIE, and PHI. Accessing 49 total economies requires using the broader query tool.

Connections rely on a zero-trust architecture. Vinkius isolates the execution of your macroeconomic data requests, meaning no internal Google Cloud credentials ever leave your infrastructure.

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