Skip to main content
Glama
jneless
by jneless

tos_delete_bucket

Delete a TOS storage bucket to remove unused containers and manage cloud storage resources efficiently.

Instructions

删除 TOS 存储桶

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bucket_nameYes存储桶名称

Implementation Reference

  • The main handler function that implements the tos_delete_bucket tool. It extracts the bucket_name from input arguments and calls tos_client.delete_bucket to perform the deletion, returning success or error message.
    async def delete_bucket(args: Dict[str, Any]) -> List[TextContent]:
        """删除存储桶"""
        bucket_name = args["bucket_name"]
        
        try:
            tos_client.delete_bucket(bucket_name)
            return [TextContent(type="text", text=f"成功删除存储桶: {bucket_name}")]
        except Exception as e:
            return [TextContent(type="text", text=f"删除存储桶失败: {str(e)}")]
  • The input schema definition for the tos_delete_bucket tool, specifying bucket_name as a required string parameter.
    inputSchema={
        "type": "object",
        "properties": {
            "bucket_name": {
                "type": "string",
                "description": "存储桶名称"
            }
        },
        "required": ["bucket_name"]
    }
  • Tool dispatch registration in the call_tool handler, mapping 'tos_delete_bucket' to the delete_bucket function.
    elif name == "tos_delete_bucket":
        return await delete_bucket(arguments)
  • Tool registration in list_tools, defining name, description, and schema for tos_delete_bucket.
    Tool(
        name="tos_delete_bucket",
        description="删除 TOS 存储桶",
        inputSchema={
            "type": "object",
            "properties": {
                "bucket_name": {
                    "type": "string",
                    "description": "存储桶名称"
                }
            },
            "required": ["bucket_name"]
        }
    ),

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jneless/tos-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server