Asset Panda 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 Asset Panda 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="Asset Panda Assistant",
instructions=(
"You help users interact with Asset Panda. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Asset Panda"
)
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 Asset Panda MCP Server
The Asset Panda MCP Server provides a flexible natural language interface to your asset tracking and management platform. Empower your AI agent to manage your entire inventory, from high-level entity groups to individual asset details and location tracking.
The OpenAI Agents SDK auto-discovers all 8 tools from Asset Panda through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Asset Panda, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
Key Features
- Group Management — List all organizational entities (Groups) to understand how your data is structured.
- Asset Tracking — Retrieve detailed information for individual objects (assets), including custom field values.
- Inventory Oversight — List and search for assets within specific groups to maintain an accurate inventory.
- Asset Lifecycle — Create and update asset records directly from your chat interface to reflect real-world changes instantly.
- Location Management — Track where your assets are across different sites and departments.
- Secure OAuth 2.0 — Uses secure Client Credentials flow to ensure safe access to your organization's inventory data.
The Asset Panda 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 Asset Panda to OpenAI Agents SDK via MCP
Follow these steps to integrate the Asset Panda 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 Asset Panda
Why Use OpenAI Agents SDK with the Asset Panda MCP Server
OpenAI Agents SDK provides unique advantages when paired with Asset Panda 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
Asset Panda + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Asset Panda MCP Server delivers measurable value.
Automated workflows: build agents that query Asset Panda, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Asset Panda, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Asset Panda tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Asset Panda to resolve tickets, look up records, and update statuses without human intervention
Asset Panda MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect Asset Panda to OpenAI Agents SDK via MCP:
create_object
Create a new object (asset) in a group
get_account_check
Verify Asset Panda account connection
get_group
Get metadata for a specific asset group
get_object
Get details for a specific object (asset)
list_groups
List all asset groups (entities) in Asset Panda
list_locations
List all locations (alias for list_groups)
list_objects
List all objects (assets) within a specific group
update_object
Update an existing object (asset)
Example Prompts for Asset Panda in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Asset Panda immediately.
"List all asset groups in my account."
"Show me the assets in the 'Laptops' group (ID: 12345)."
"Update the status of asset 'obj_9988' in group '123' to 'In Repair'."
Troubleshooting Asset Panda MCP Server with OpenAI Agents SDK
Common issues when connecting Asset Panda to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Asset Panda + OpenAI Agents SDK FAQ
Common questions about integrating Asset Panda 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 Asset Panda 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 Asset Panda to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.
