blob_list
Retrieve and list blobs stored in a specified Azure Blob Storage container using the Azure MCP Server for streamlined data management and audit tracking.
Instructions
List blobs in a Blob Storage container
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| container_name | Yes | Name of the Blob Storage container |
Input Schema (JSON Schema)
{
"properties": {
"container_name": {
"description": "Name of the Blob Storage container",
"type": "string"
}
},
"required": [
"container_name"
],
"type": "object"
}
Implementation Reference
- mcp_server_azure/azure_server.py:212-218 (handler)Handler logic for 'blob_list' tool: retrieves the container client, lists blobs, extracts names, and prepares response.elif name == "blob_list": container_client = blob_service_client.get_container_client( arguments["container_name"] ) blob_list = container_client.list_blobs() blob_names = [blob.name for blob in blob_list] response = {"blob_names": blob_names}
- Schema definition for 'blob_list' tool, specifying input as object with required 'container_name' string.Tool( name="blob_list", description="List blobs in a Blob Storage container", inputSchema={ "type": "object", "properties": { "container_name": { "type": "string", "description": "Name of the Blob Storage container", } }, "required": ["container_name"], }, ),
- mcp_server_azure/azure_server.py:171-176 (registration)Registers the tools including 'blob_list' by returning get_azure_tools() in the list_tools handler.@server.list_tools() async def list_tools() -> list[Tool]: """List available Azure tools""" logger.debug("Handling list_tools request") return get_azure_tools() # Use get_azure_tools