How to Use the Azure Blob Container MCP in AutoGen

Q: How does AutoGen handle Azure Blob Container lists?

The agents use listblobs to see what is inside the container. They then discuss the file list to decide which ones to process.

Let your AutoGen agents debate file tasks using the Azure Blob Container MCP Server.

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Connect Azure Blob Container MCP to AutoGen

Create your Vinkius account to connect Azure Blob Container to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Azure Blob Container with AutoGen

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AutoGen agents managing Azure Blob Container

Create a multi-agent system where one agent proposes a file change and another verifies it. Use `put_blob` to commit changes once the agents agree. This debate-based approach reduces errors. You get a consensus-driven workflow for your storage operations.

Debate-driven storage in AutoGen

Agents use `list_blobs` to survey the container before acting. They discuss which files to modify or delete based on the current system state. This prevents accidental changes. The agents negotiate the best course of action before calling any destructive tools.

Secure file interaction for AutoGen

The security agent can audit proposed file operations. If it flags a `delete_blob` request, the agents must resolve the conflict before the file is removed. This adds a layer of human-like caution to your automated storage tasks. You define the agents and they handle the deliberation.

Setup guide

Set up Azure Blob Container MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Azure Blob Container tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Azure Blob Container_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Azure Blob Container data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Azure Blob Container_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Azure Blob Container data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Azure Blob Container. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Azure Blob Container MCP in AutoGen

The MCP adapter translates tools into functions your agents can call. They treat file management as a collaborative task.

You control the agent's access by what tools you provide. If you omit the `delete_blob` tool, the agents cannot execute that command.

The agents use `list_blobs` to see what is inside the container. They then discuss the file list to decide which ones to process.

No, the MCP server handles authentication internally. The agents only interact with the tools provided by the server.

All file data is processed within your isolated session. The agent's conversation history does not expose your storage credentials to external parties.

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