Can the AI really create and download a pre-signed link from Veraset's S3 directly?

Yes. Upon using the `generateDownloadLinkTool`, the agent will interface via Veraset's protocol using your API token, instantly retrieving an authenticated, time-sensitive download link to let you extract the immense dataset files securely.

What happens if a SQL statement to Veraset starts taking too long?

You don't need to panic or swap tools. Instruct your agent: `cancel the running query id 'query-xx9'`, and the `cancelQueryTool` fires an immediate abort network call. The computation ends, saving extensive costs without abandoning the conversational flow.

How can I preview geolocation signals before compiling expensive queries?

Ask for the `getSchemaTool` followed by `getSampleTool`. The AI perfectly delivers the dataset definitions and outputs five physical preview rows right inside your message history, confirming expected structure formatting.

Veraset MCP Server for Google ADK 10 tools — connect in under 2 minutes

Name: Veraset
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Veraset as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="veraset_agent",
    instruction=(
        "You help users interact with Veraset "
        "using 10 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

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IAMAccess control

EU AI ActCompliant

DLPData protection

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Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Veraset MCP Server

Bind the massive scale of Veraset geolocation data directly to your preferred AI conversational agent. Eradicate context switching when analyzing billions of Points of Interest (POI) and mobile signal attributes.

Google ADK natively supports Veraset as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Live SQL Querying — Prompt your LLM agent to construct, dispatch, and execute ANSI SQL directly aimed at Veraset databases to compute geolocation aggregates.
Rapid Execution Management — Check on long-running geolocation jobs, pull back the output tables seamlessly, or ruthlessly cancel intensive queries straight from your text box.
Dataset Profiling — Scan all your available Veraset packages, request quick dataset schemas, or instantly preview data samples to ensure accuracy before executing queries.
Delivery Bucket Access — Query the secure S3 delivery prefixes attached to your organization for bulk downloads and dynamically generate pre-signed file keys in seconds.

The Veraset MCP Server exposes 10 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Veraset to Google ADK via MCP

Follow these steps to integrate the Veraset MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 10 tools from Veraset via MCP

Why Use Google ADK with the Veraset MCP Server

Google ADK provides unique advantages when paired with Veraset through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Veraset

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Veraset tools with BigQuery, Vertex AI, and Cloud Functions

Veraset + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Veraset MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Veraset and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Veraset tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Veraset regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Veraset

Veraset MCP Tools for Google ADK (10)

These 10 tools become available when you connect Veraset to Google ADK via MCP:

cancel_running_query

Immediately aborts a currently executing SQL task

execute_sql_query

Provide a dataset ID and ANSI SQL. Returns a query ID. Starts a new SQL query task against a Veraset dataset

generate_download_link

Generates a temporary pre-signed URL for an S3 file download

get_dataset_metadata

Retrieves technical metadata for a specific mobility dataset

get_dataset_sample

Retrieves a quick sample of the first few rows of a dataset

get_dataset_schema

Retrieves the column definitions and data types for a dataset

get_query_results

Supports pagination. Retrieves the result rows from a completed SQL query

get_query_status

Checks the progress of a running SQL query

list_mobility_datasets

Identify accessible mobility datasets in Veraset

list_s3_delivery_folders

Lists S3 prefixes where scheduled data drops are delivered

Example Prompts for Veraset in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Veraset immediately.

"List all our provisioned delivery folder buckets for S3 mobility packets."

"Get a basic preview 10-row sample from the dataset 'movement_global'."

"Execute an aggregation query on 'dataset-v5' grouping total foot traffic by 'store_id' and get the current execution status."

Troubleshooting Veraset MCP Server with Google ADK

Common issues when connecting Veraset to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Veraset + Google ADK FAQ

Common questions about integrating Veraset MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.