Parknav MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Parknav through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Parknav Assistant",
instructions=(
"You help users interact with Parknav. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Parknav"
)
print(result.final_output)
asyncio.run(main())
* 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 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.
The OpenAI Agents SDK auto-discovers all 8 tools from Parknav through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Parknav, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the Parknav MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 8 tools from Parknav
Why Use OpenAI Agents SDK with the Parknav MCP Server
OpenAI Agents SDK provides unique advantages when paired with Parknav through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Parknav + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Parknav MCP Server delivers measurable value.
Automated workflows: build agents that query Parknav, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Parknav, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Parknav tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Parknav to resolve tickets, look up records, and update statuses without human intervention
Parknav MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect Parknav to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting Parknav to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Parknav + OpenAI Agents SDK FAQ
Common questions about integrating Parknav MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Parknav with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Parknav to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.