How to Use the Aliyun OSS / 阿里云对象存储 MCP in Google ADK

Q: Can Gemini read text files from Aliyun OSS / 阿里云对象存储 through Google ADK?

It works perfectly for that. The model calls downloadobjecttext to pull raw text or JSON payloads straight into its context window for immediate analysis.

Q: How large of a file can the agent upload via this MCP Server?

The uploadobject tool handles up to 5GB per request. It pushes text content directly into your specified bucket path.

Give your Gemini models direct read and write access to Aliyun OSS buckets using Google ADK.

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Connect Aliyun OSS / 阿里云对象存储 MCP to Google ADK

Create your Vinkius account to connect Aliyun OSS / 阿里云对象存储 to Google ADK 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 Aliyun OSS / 阿里云对象存储 with Google ADK

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Perplexity

Feed object data into long-context reasoning

Gemini thrives on massive datasets. By connecting this MCP Server, your agent pulls huge JSON logs directly from storage using the `download_object_text` tool. The model consumes that entire text payload in one shot. It analyzes patterns, cross-references internal logic, and pushes insights back via `upload_object`.

Audit bucket configurations with Google ADK

Enterprise agents need situational awareness before modifying infrastructure. They run `get_bucket_location` to confirm data residency requirements in regions like oss-cn-hangzhou. From there, the system checks permissions via `get_bucket_acl`. You get a clear picture of your storage security posture routed straight into your Vertex AI pipeline through this MCP integration.

Filter and manage massive directories

Finding specific files across millions of objects requires precision. The agent executes `list_objects` with specific prefix paths to isolate exact directories without scanning the whole bucket. Once located, the model inspects individual file details using `get_object_metadata`. It then triggers `delete_object` to purge outdated records based on your custom retention logic.

Setup guide

Set up Aliyun OSS / 阿里云对象存储 MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Aliyun OSS / 阿里云对象存储 tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Aliyun OSS / 阿里云对象存储_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Aliyun OSS / 阿里云对象存储 tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Aliyun OSS / 阿里云对象存储. 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 Aliyun OSS / 阿里云对象存储 MCP in Google ADK

Run pip install google-adk first. Wrap your Vinkius endpoint in a StreamableHttpServerParameters object, pass it to McpToolset, and attach that to your LlmAgent.

It works perfectly for that. The model calls `download_object_text` to pull raw text or JSON payloads straight into its context window for immediate analysis.

You retain full control over exposed operations. Use the tool_names filter in your McpToolset configuration to expose only safe operations like `get_bucket_info` while hiding deletion tools.

The `upload_object` tool handles up to 5GB per request. It pushes text content directly into your specified bucket path.

Vinkius handles authentication server-side via a single endpoint token. Your local environment never holds the raw Aliyun keys, keeping your infrastructure credentials isolated.

Use it with your favorite AI tools

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