Tencent COS / 腾讯云对象存储 MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Tencent COS / 腾讯云对象存储 through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
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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="Tencent COS / 腾讯云对象存储 Assistant",
instructions=(
"You help users interact with Tencent COS / 腾讯云对象存储. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Tencent COS / 腾讯云对象存储"
)
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 Tencent COS / 腾讯云对象存储 MCP Server
Empower your AI agent to orchestrate your cloud storage infrastructure and asset management with Tencent COS (对象存储), the premier storage service in China. By connecting Tencent COS to your agent, you transform complex file operations, metadata auditing, and storage lifecycle management into a natural conversation. Your agent can instantly upload text assets, retrieve detailed object headers, list directory contents with delimiter support, and monitor storage status without you ever needing to navigate the comprehensive Tencent Cloud Console. Whether you are conducting a digital asset audit or coordinating a content update, your agent acts as a real-time cloud storage coordinator, providing accurate results from a single, authorized source.
The OpenAI Agents SDK auto-discovers all 10 tools from Tencent COS / 腾讯云对象存储 through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Tencent COS / 腾讯云对象存储, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Asset Orchestration — Upload, delete, and manage text-based objects across your Tencent COS buckets.
- Metadata Auditing — Retrieve detailed HTTP headers and verify object existence through secure metadata queries.
- Inventory Control — List objects with advanced filtering (prefix, delimiter) to organize your storage structure.
- Public URL Generation — Automatically generate public endpoints for your shared cloud assets.
- System Monitoring — Verify bucket configuration and API connectivity to ensure operational continuity.
The Tencent COS / 腾讯云对象存储 MCP Server exposes 10 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 Tencent COS / 腾讯云对象存储 to OpenAI Agents SDK via MCP
Follow these steps to integrate the Tencent COS / 腾讯云对象存储 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 10 tools from Tencent COS / 腾讯云对象存储
Why Use OpenAI Agents SDK with the Tencent COS / 腾讯云对象存储 MCP Server
OpenAI Agents SDK provides unique advantages when paired with Tencent COS / 腾讯云对象存储 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
Tencent COS / 腾讯云对象存储 + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Tencent COS / 腾讯云对象存储 MCP Server delivers measurable value.
Automated workflows: build agents that query Tencent COS / 腾讯云对象存储, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Tencent COS / 腾讯云对象存储, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Tencent COS / 腾讯云对象存储 tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Tencent COS / 腾讯云对象存储 to resolve tickets, look up records, and update statuses without human intervention
Tencent COS / 腾讯云对象存储 MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Tencent COS / 腾讯云对象存储 to OpenAI Agents SDK via MCP:
check_object_exists
Check if an object exists
copy_object
Copy an object within the bucket
delete_object
Delete an object from COS
download_object_text
Download an object as text
get_bucket_acl
Get bucket access permissions
get_object_metadata
Get object metadata (HEAD)
head_bucket
Check if the bucket exists and is accessible
list_objects
Use prefix to filter by path. List objects in the COS bucket
list_root_objects
List top-level objects and folders
upload_object
Max 5GB per request. Upload text content to COS
Example Prompts for Tencent COS / 腾讯云对象存储 in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Tencent COS / 腾讯云对象存储 immediately.
"List all files in the root of my Tencent COS bucket."
"Check if the file 'backups/db_init.sql' exists in COS."
"Get the metadata for 'static/css/main.css'."
Troubleshooting Tencent COS / 腾讯云对象存储 MCP Server with OpenAI Agents SDK
Common issues when connecting Tencent COS / 腾讯云对象存储 to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Tencent COS / 腾讯云对象存储 + OpenAI Agents SDK FAQ
Common questions about integrating Tencent COS / 腾讯云对象存储 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 Tencent COS / 腾讯云对象存储 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 Tencent COS / 腾讯云对象存储 to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.