mcpbeat Sign in

Azure Servicebus Py Agent Skill

| Azure Service Bus SDK for Python messaging. Use for queues, topics, subscriptions, and enterprise messaging patterns.

13k tokens
context cost
the whole folder, loaded on every use
4
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
123 d ago
last touched
this folder, not the whole repository

Install

one command, takes just this skill from the repository
npx skills add https://github.com/microsoft/skills --skill azure-servicebus-py

What comes with it

41 342 bytes besides the instruction
references/dead-letter.md
references/patterns.md
scripts/setup_servicebus.py

The instruction itself

16 sections, as written by the author

Azure Service Bus SDK for Python

Enterprise messaging for reliable cloud communication with queues and pub/sub topics.

Installation

pip install azure-servicebus azure-identity

Environment Variables

SERVICEBUS_FULLY_QUALIFIED_NAMESPACE=<namespace>.servicebus.windows.net  # Required for all auth methods
SERVICEBUS_QUEUE_NAME=myqueue  # Required for queue operations
SERVICEBUS_TOPIC_NAME=mytopic  # Required for topic operations
SERVICEBUS_SUBSCRIPTION_NAME=mysubscription  # Required for subscription operations
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication & Lifecycle

> 🔑 Two rules apply to every code sample below:

>

> 1. Prefer DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.

> - Local dev: DefaultAzureCredential works as-is.

> - Production: set AZURE_TOKEN_CREDENTIALS=prod (or AZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.

> 2. Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:

> - Sync: with <Client>(...) as client:

> - Async: async with <Client>(...) as client: and async with DefaultAzureCredential() as credential: (from azure.identity.aio)

>

> Snippets may abbreviate this setup, but production code should always follow both rules.

from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.servicebus import ServiceBusClient

# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
namespace = "<namespace>.servicebus.windows.net"

with ServiceBusClient(
    fully_qualified_namespace=namespace,
    credential=credential
) as client:
    # Use client here (see following sections for operations)
    ...

Client Types

| Client | Purpose | Get From |

|--------|---------|----------|

| ServiceBusClient | Connection management | Direct instantiation |

| ServiceBusSender | Send messages | client.get_queue_sender() / get_topic_sender() |

| ServiceBusReceiver | Receive messages | client.get_queue_receiver() / get_subscription_receiver() |

Send Messages (Async)

import asyncio
from azure.servicebus.aio import ServiceBusClient
from azure.servicebus import ServiceBusMessage
from azure.identity.aio import DefaultAzureCredential

async def send_messages():
    credential = DefaultAzureCredential()
    
    async with ServiceBusClient(
        fully_qualified_namespace="<namespace>.servicebus.windows.net",
        credential=credential
    ) as client:
        sender = client.get_queue_sender(queue_name="myqueue")
        
        async with sender:
            # Single message
            message = ServiceBusMessage("Hello, Service Bus!")
            await sender.send_messages(message)
            
            # Batch of messages
            messages = [ServiceBusMessage(f"Message {i}") for i in range(10)]
            await sender.send_messages(messages)
            
            # Message batch (for size control)
            batch = await sender.create_message_batch()
            for i in range(100):
                try:
                    batch.add_message(ServiceBusMessage(f"Batch message {i}"))
                except ValueError:  # Batch full
                    await sender.send_messages(batch)
                    batch = await sender.create_message_batch()
                    batch.add_message(ServiceBusMessage(f"Batch message {i}"))
            await sender.send_messages(batch)

asyncio.run(send_messages())

Receive Messages (Async)

async def receive_messages():
    credential = DefaultAzureCredential()
    
    async with ServiceBusClient(
        fully_qualified_namespace="<namespace>.servicebus.windows.net",
        credential=credential
    ) as client:
        receiver = client.get_queue_receiver(queue_name="myqueue")
        
        async with receiver:
            # Receive batch
            messages = await receiver.receive_messages(
                max_message_count=10,
                max_wait_time=5  # seconds
            )
            
            for msg in messages:
                print(f"Received: {str(msg)}")
                await receiver.complete_message(msg)  # Remove from queue

asyncio.run(receive_messages())

Receive Modes

| Mode | Behavior | Use Case |

|------|----------|----------|

| PEEK_LOCK (default) | Message locked, must complete/abandon | Reliable processing |

| RECEIVE_AND_DELETE | Removed immediately on receive | At-most-once delivery |

from azure.servicebus import ServiceBusReceiveMode

receiver = client.get_queue_receiver(
    queue_name="myqueue",
    receive_mode=ServiceBusReceiveMode.RECEIVE_AND_DELETE
)

Message Settlement

async with receiver:
    messages = await receiver.receive_messages(max_message_count=1)
    
    for msg in messages:
        try:
            # Process message...
            await receiver.complete_message(msg)  # Success - remove from queue
        except ProcessingError:
            await receiver.abandon_message(msg)  # Retry later
        except PermanentError:
            await receiver.dead_letter_message(
                msg,
                reason="ProcessingFailed",
                error_description="Could not process"
            )

| Action | Effect |

|--------|--------|

| complete_message() | Remove from queue (success) |

| abandon_message() | Release lock, retry immediately |

| dead_letter_message() | Move to dead-letter queue |

| defer_message() | Set aside, receive by sequence number |

Topics and Subscriptions

# Send to topic
sender = client.get_topic_sender(topic_name="mytopic")
async with sender:
    await sender.send_messages(ServiceBusMessage("Topic message"))

# Receive from subscription
receiver = client.get_subscription_receiver(
    topic_name="mytopic",
    subscription_name="mysubscription"
)
async with receiver:
    messages = await receiver.receive_messages(max_message_count=10)

Sessions (FIFO)

# Send with session
message = ServiceBusMessage("Session message")
message.session_id = "order-123"
await sender.send_messages(message)

# Receive from specific session
receiver = client.get_queue_receiver(
    queue_name="session-queue",
    session_id="order-123"
)

# Receive from next available session
from azure.servicebus import NEXT_AVAILABLE_SESSION
receiver = client.get_queue_receiver(
    queue_name="session-queue",
    session_id=NEXT_AVAILABLE_SESSION
)

Scheduled Messages

from datetime import datetime, timedelta, timezone

message = ServiceBusMessage("Scheduled message")
scheduled_time = datetime.now(timezone.utc) + timedelta(minutes=10)

# Schedule message
sequence_number = await sender.schedule_messages(message, scheduled_time)

# Cancel scheduled message
await sender.cancel_scheduled_messages(sequence_number)

Dead-Letter Queue

from azure.servicebus import ServiceBusSubQueue

# Receive from dead-letter queue
dlq_receiver = client.get_queue_receiver(
    queue_name="myqueue",
    sub_queue=ServiceBusSubQueue.DEAD_LETTER
)

async with dlq_receiver:
    messages = await dlq_receiver.receive_messages(max_message_count=10)
    for msg in messages:
        print(f"Dead-lettered: {msg.dead_letter_reason}")
        await dlq_receiver.complete_message(msg)

Sync Client (for simple scripts)

from azure.servicebus import ServiceBusClient, ServiceBusMessage
from azure.identity import DefaultAzureCredential

with ServiceBusClient(
    fully_qualified_namespace="<namespace>.servicebus.windows.net",
    credential=DefaultAzureCredential()
) as client:
    with client.get_queue_sender("myqueue") as sender:
        sender.send_messages(ServiceBusMessage("Sync message"))
    
    with client.get_queue_receiver("myqueue") as receiver:
        for msg in receiver:
            print(str(msg))
            receiver.complete_message(msg)

Best Practices

  • Pick sync OR async and stay consistent. Do not mix azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose one mode per module.
  • Always use context managers for clients and async credentials. Wrap every client in with Client(...) as client: (sync) or async with Client(...) as client: (async) for proper cleanup. For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.
  • Use DefaultAzureCredential for portable auth across local dev and Azure (avoid connection strings / API keys when possible).
  • Use async client for production workloads
  • Complete messages after successful processing
  • Use dead-letter queue for poison messages
  • Use sessions for ordered, FIFO processing
  • Use message batches for high-throughput scenarios
  • Set max_wait_time to avoid infinite blocking

Reference Files

| File | Contents |

|------|----------|

| references/patterns.md | Competing consumers, sessions, retry patterns, request-response, transactions |

| references/dead-letter.md | DLQ handling, poison messages, reprocessing strategies |

| scripts/setup_servicebus.py | CLI for queue/topic/subscription management and DLQ monitoring |

Other skills for the same job

different authors, same section of the catalogue
Modal
by christophacham
×3

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

17k tokens
Github Workflow Automation
by ComeOnOliver
×3

Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

9k tokens
Gcloud
by Dicklesworthstone
×2

Google Cloud Platform CLI - manage GCP resources including Compute Engine, Cloud Run, GKE, Cloud Functions, Storage, BigQuery, and more.

2k tokens
Backend Architect
by ComeOnOliver
×2

Expert backend architect specializing in scalable API design, microservices architecture, and distributed systems. Masters REST/GraphQL/gRPC APIs, event-driven architectures, service mesh patterns, and modern backend frameworks. Handles service boundary definition, inter-service communication, resilience patterns, and observability. Use PROACTIVELY when creating new backend services or APIs.

7k tokens
Modal
by ComeOnOliver
×2

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

37k tokens
Aspire
by github
vendor ×1

Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application.

21k tokens
Bigquery Pipeline Audit
by github
vendor ×1

Audits Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations.

1k tokens
Msstore CLI
by github
vendor ×1

Microsoft Store Developer CLI (msstore) for publishing Windows applications to the Microsoft Store. Use when asked to configure Store credentials, list Store apps, check submission status, publish submissions, manage package flights, set up CI/CD for Store publishing, or integrate with Partner Center. Supports Windows App SDK/WinUI, UWP, .NET MAUI, Flutter, Electron, React Native, and PWA applications.

4k tokens

How to use it

Copy the folder

Take microsoft/azure-servicebus-py from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip. Without those the skill loads but fails at the first command.