SenseCore Platform MCP Server for OpenAI Agents SDK 11 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect SenseCore Platform 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="SenseCore Platform Assistant",
instructions=(
"You help users interact with SenseCore Platform. "
"You have access to 11 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from SenseCore Platform"
)
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 SenseCore Platform MCP Server
Connect your AI agents to the SenseCore Platform, the industrial-grade AI infrastructure by SenseTime. This MCP provides 10 tools to manage advanced foundation models, orchestrate large-scale chat completions, and monitor high-performance compute resources programmatically.
The OpenAI Agents SDK auto-discovers all 11 tools from SenseCore Platform through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries SenseCore Platform, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- SenseChat Interaction — Trigger chat completions with SenseTime's foundation models using persistent context and history
- Model Intelligence — List all available foundation models and retrieve granular technical specifications for each version
- Resource Management — Monitor compute node availability and track quota consumption across your organizational projects
- Service Monitoring — Check real-time health and latency metrics for deployed model services
- Async Operations — List and track the status of long-running training or inference tasks on the SenseCore infrastructure
The SenseCore Platform MCP Server exposes 11 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 SenseCore Platform to OpenAI Agents SDK via MCP
Follow these steps to integrate the SenseCore Platform 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 11 tools from SenseCore Platform
Why Use OpenAI Agents SDK with the SenseCore Platform MCP Server
OpenAI Agents SDK provides unique advantages when paired with SenseCore Platform 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
SenseCore Platform + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the SenseCore Platform MCP Server delivers measurable value.
Automated workflows: build agents that query SenseCore Platform, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries SenseCore Platform, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through SenseCore Platform tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query SenseCore Platform to resolve tickets, look up records, and update statuses without human intervention
SenseCore Platform MCP Tools for OpenAI Agents SDK (11)
These 11 tools become available when you connect SenseCore Platform to OpenAI Agents SDK via MCP:
chat_completions
Send a message to a SenseCore large language model
create_assistant
Define a new AI assistant
create_message
Add a message to a thread
create_run
Execute an assistant on a thread
create_thread
Initialize a new conversation thread
get_assistant_details
Get complete configuration for an assistant
get_run_status
Check the status of an active assistant run
list_assistants
List all configured assistants
list_files
List uploaded files
list_messages
Retrieve the message history of a thread
list_models
List all available SenseNova models
Example Prompts for SenseCore Platform in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with SenseCore Platform immediately.
"Chat with SenseChat-5 and ask 'Compare the features of traditional neural networks and transformers'."
"List all active models in project 'Research_AI_2024'."
"What is the health status of service ID 'svc_gpu_999'?"
Troubleshooting SenseCore Platform MCP Server with OpenAI Agents SDK
Common issues when connecting SenseCore Platform to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
SenseCore Platform + OpenAI Agents SDK FAQ
Common questions about integrating SenseCore Platform 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 SenseCore Platform 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 SenseCore Platform to OpenAI Agents SDK
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.