How to Use the Namsor Alternative MCP in Google ADK

Q: How do I integrate Namsor Alternative with Google ADK?

Install google-adk via pip. Initialize an McpToolset with your Vinkius HTTP URL and assign it to the tools array in your LlmAgent.

Q: How do I restrict which tools the agent can use?

Pass the toolnames parameter when configuring your toolset. This prevents the agent from calling endpoints like getgender if you only need phone formatting.

Run onomastic analysis on BigQuery datasets using Google ADK and Gemini's long-context reasoning.

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Connect Namsor Alternative MCP to Google ADK

Create your Vinkius account to connect Namsor Alternative 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 Namsor Alternative with Google ADK

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Classify names with the Google ADK MCP Server

The `get_us_race_ethnicity` and `get_origin` tools predict demographic categories from raw text. You pass a name string to the endpoint. It maps the input against US Census distributions or surname prefixes to return a classification. Gemini models can hold millions of tokens. You can feed massive BigQuery contact lists into your `LlmAgent`. The agent iterates through the records, applying the classification tools to segment your audience without leaving the Google Cloud ecosystem.

Structure raw text fields

The `parse_name` tool splits a single string into distinct components like first name, middle initial, and surname. Your agent reads a messy CRM export. It calls the parser for every row to normalize the formatting. You set up the connection using `McpToolset` with `StreamableHttpServerParameters`. If you only want the agent to parse names and ignore the demographic tools, use the `tool_names` filter to restrict access.

Standardize contact details

The `format_phone` tool validates numbers into E.164 format, and `get_gender` infers male or female categories from first names. A Vertex AI pipeline triggers the agent. It cleans the inputs before writing the final records back to your database. Vinkius handles the underlying infrastructure. You just need one endpoint token to connect the MCP integration. The server executes the logic in an isolated environment, keeping your enterprise workflows fast and predictable.

Setup guide

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

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Common questions about Namsor Alternative MCP in Google ADK

Install `google-adk` via pip. Initialize an `McpToolset` with your Vinkius HTTP URL and assign it to the `tools` array in your `LlmAgent`.

Yes. Your agent can read rows from BigQuery, use the server to parse names or format phone numbers, and write the cleaned data back.

Pass the `tool_names` parameter when configuring your toolset. This prevents the agent from calling endpoints like `get_gender` if you only need phone formatting.

Gemini can process massive datasets in a single prompt. The agent will batch-call the MCP tools for thousands of names natively.

The server handles raw names and phone numbers. Vinkius operates a zero-trust architecture where every request runs in a temporary sandbox that is wiped immediately after execution.

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