How far in advance can Parknav predict availability?

Parknav's AI can typically predict availability up to 24 hours in advance with high confidence, and up to 7 days with moderate confidence.

Does it cover off-street garages too?

Parknav primarily focuses on on-street parking, but also integrates occupancy data from select off-street garages where sensors are available.

What data sources does Parknav use?

Parknav combines IoT sensor data, historical trends, city event data, and weather patterns using deep learning models to generate its predictions.

Parknav MCP Server for Google ADK 8 tools — connect in under 2 minutes

Name: Parknav
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 8 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Parknav 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

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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="parknav_agent",
    instruction=(
        "You help users interact with Parknav "
        "using 8 available tools."
    ),
    tools=[mcp_tools],
)

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About Parknav MCP Server

Connect Parknav to any AI agent and access the world's most advanced predictive parking intelligence — anticipate availability before you arrive, find on-street spots instantly, and optimize your urban mobility.

Google ADK natively supports Parknav as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 8 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

Predictive Availability — Get AI forecasts for finding a spot at a specific future time
Real-Time Occupancy — Check current block-by-block occupancy rates
Nearest Spot Finder — Get directed to the nearest currently open space
Street Segments — View live status of specific street blocks
Zone Regulations — Access parking rules, time limits, and pricing
Historical Trends — Analyze availability patterns by time of day and day of week
Route Optimization — Plan routes that minimize parking search time

The Parknav MCP Server exposes 8 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 Parknav to Google ADK via MCP

Follow these steps to integrate the Parknav 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 8 tools from Parknav via MCP

Why Use Google ADK with the Parknav MCP Server

Google ADK provides unique advantages when paired with Parknav 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 Parknav

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 Parknav tools with BigQuery, Vertex AI, and Cloud Functions

Parknav + Google ADK Use Cases

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

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

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

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

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

Parknav MCP Tools for Google ADK (8)

These 8 tools become available when you connect Parknav to Google ADK via MCP:

get_city_insights

Get high-level parking insights for a specific city

get_historical_trends

Get historical availability trends for a location

get_nearest_spot

Find the nearest currently available parking spot

get_parking_zones

Get regulations and pricing for parking zones

get_realtime_occupancy

Get current real-time occupancy for a location

get_street_segments

Get status of street segments for on-street parking

optimize_parking_route

Optimize a route to include the best parking options

predict_availability

Essential for planning trips in advance. Get AI-predicted parking availability for a location at a specific time

Example Prompts for Parknav in Google ADK

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

"Will I find parking near Union Square at 6 PM?"

"Where is the nearest open spot to me right now?"

"Show me the occupancy trends for Market Street."

Troubleshooting Parknav MCP Server with Google ADK

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

McpToolset not found

Update: pip install --upgrade google-adk

Parknav + Google ADK FAQ

Common questions about integrating Parknav 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.