Arrivy MCP Server for OpenAI Agents SDK 9 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Arrivy 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="Arrivy Assistant",
instructions=(
"You help users interact with Arrivy. "
"You have access to 9 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Arrivy"
)
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 Arrivy MCP Server
The Arrivy MCP Server empowers your AI agent to coordinate field operations and last-mile delivery directly from your workspace. Seamlessly manage your mobile workforce, track job progress, and engage with customers using natural language.
The OpenAI Agents SDK auto-discovers all 9 tools from Arrivy through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Arrivy, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
Key Features
- Task Orchestration — List, create, and update service tasks or delivery jobs with real-time status tracking.
- Crew Management — Monitor field personnel and resource assignments to ensure efficient job allocation.
- Customer Engagement — Manage customer records and sync service history for better communication.
- Location Tracking — Access real-time location data and ETAs for your field technicians and delivery drivers.
- Digital Workflow — Access data captured in the field, including forms, photos, and status updates.
- Seamless Integration — Connect your Arrivy operations with your AI-assisted project management and support workflows.
Benefits for Teams
- Operations Managers — Quickly audit active jobs and crew statuses without leaving your AI dashboard.
- Dispatchers — Use AI to quickly create and assign new tasks based on customer requests.
- Customer Success — Retrieve job history and ETAs instantly to provide accurate updates to clients.
The Arrivy MCP Server exposes 9 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 Arrivy to OpenAI Agents SDK via MCP
Follow these steps to integrate the Arrivy 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 9 tools from Arrivy
Why Use OpenAI Agents SDK with the Arrivy MCP Server
OpenAI Agents SDK provides unique advantages when paired with Arrivy 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
Arrivy + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Arrivy MCP Server delivers measurable value.
Automated workflows: build agents that query Arrivy, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Arrivy, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Arrivy tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Arrivy to resolve tickets, look up records, and update statuses without human intervention
Arrivy MCP Tools for OpenAI Agents SDK (9)
These 9 tools become available when you connect Arrivy to OpenAI Agents SDK via MCP:
create_customer
Create a new customer record
create_task
Create a new service task in Arrivy
get_account_check
Verify Arrivy account connection
get_task
Get details for a specific task
list_crews
List all field crews and personnel
list_customers
List all customers in the system
list_locations
List all tracked locations
list_tasks
List all service tasks in Arrivy
update_task
Update an existing service task
Example Prompts for Arrivy in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Arrivy immediately.
"List all scheduled tasks for today in Arrivy."
"Create a new task 'Emergency Leak Repair' at '123 Maple St'."
"Show me the status of task ID 'T12345'."
Troubleshooting Arrivy MCP Server with OpenAI Agents SDK
Common issues when connecting Arrivy to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Arrivy + OpenAI Agents SDK FAQ
Common questions about integrating Arrivy 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 Arrivy 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 Arrivy to OpenAI Agents SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.