Can the AI push routes dynamically to drivers' smartphones automatically?

Yes! Activating the `publish_route_to_driver` function dynamically interacts with the saas infrastructure, natively pushing an authorized manifest to the delivery team's active Routific phone apps flawlessly.

Does `solve_standalone_vrp` handle extremely large thousands of stops simultaneously efficiently?

For very large batches, use `solve_async_vrp_long` instead. It processes the request asynchronously and you can poll for results with `poll_async_solution`. The standalone solver is best for smaller, real-time requests.

Can the integration update a delivery job after it has been created?

Yes. Use `update_saas_job` to modify constraints, priorities, or delivery details on an existing job without having to delete and recreate it.

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

Name: Routific
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 Routific 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="routific_agent",
    instruction=(
        "You help users interact with Routific "
        "using 10 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

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 Routific MCP Server

Connect your conversational assistant directly to Routific, a premier logistics scaling platform. This integration seamlessly turns your AI into an advanced delivery dispatcher, allowing you to build multi-stop route solutions securely, manage outstanding delivery jobs, and proactively push dispatch tasks directly to drivers' mobile apps natively in one window.

Google ADK natively supports Routific 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

Automate VRP Computations — Submit basic logistics parameters (solve_standalone_vrp) or delegate massive multi-depot configurations organically (solve_async_vrp_long) and query asynchronous status returns effortlessly (poll_async_solution).
Control Saas Delivery Jobs — Tell the AI to actively audit outstanding orders (list_platform_jobs) or create fresh delivery injections accurately handling order constraints and priorities directly into the system (create_saas_job, update_saas_job).
Assemble & Publish Timelines — Review the resulting stop-by-stop ETAs securely calculated by algorithms natively inside the interface (get_route_timeline). Once completely satisfied, simply push the finalized route natively to the targeted driver's phone with an organic command (publish_route_to_driver).

The Routific 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 Routific to Google ADK via MCP

Follow these steps to integrate the Routific 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 Routific via MCP

Why Use Google ADK with the Routific MCP Server

Google ADK provides unique advantages when paired with Routific 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 Routific

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 Routific tools with BigQuery, Vertex AI, and Cloud Functions

Routific + Google ADK Use Cases

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

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

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

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

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

Routific MCP Tools for Google ADK (10)

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

cancel_saas_job

This action is irreversible. Cancels and deletes a delivery job from the platform

create_platform_route

Creates a new route plan in the platform

create_saas_job

Provide a JSON object with order details. Creates a new delivery job in the platform

get_route_timeline

Retrieves the stop-by-stop timeline for a route

list_platform_jobs

Lists all delivery jobs in the Routific platform

poll_async_solution

Polls the status of an asynchronous VRP job

publish_route_to_driver

Publishes a route to the driver's mobile app

solve_async_vrp_long

Returns a job ID for polling. Submits a large Vehicle Routing Problem for asynchronous solving

solve_standalone_vrp

Provide a JSON object with visits, fleet, and options. Solves a standalone Vehicle Routing Problem synchronously

update_saas_job

Updates an existing delivery job

Example Prompts for Routific in Google ADK

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

"List all current delivery jobs pending in the platform right now."

"Generate a standalone route resolving 4 pending visits."

"Publish the finalized route to the designated driver's mobile app."

Troubleshooting Routific MCP Server with Google ADK

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

McpToolset not found

Update: pip install --upgrade google-adk

Routific + Google ADK FAQ

Common questions about integrating Routific 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.