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azure-functions — how to use azure functions how to use azure functions, azure functions setup guide, azure functions vs aws lambda, azure functions install, what is azure functions, azure functions alternative, azure functions tutorial, azure functions best practices, azure functions serverless computing

v1.0.0
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About this Skill

Perfect for Cloud Agents needing serverless application development with Azure Functions azure-functions is a comprehensive project template for building serverless applications with Azure Functions, supporting event-driven computing and various triggers.

Features

Creates a function app with Azure Functions
Supports HTTP trigger, timer trigger, and queue trigger
Enables durable functions and orchestration
Uses function binding and function.json configuration
Initializes storage account with az storage account create command

# Core Topics

HouseGarofalo HouseGarofalo
[0]
[0]
Updated: 3/6/2026

Quality Score

Top 5%
60
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add HouseGarofalo/claude-code-base

Agent Capability Analysis

The azure-functions MCP Server by HouseGarofalo is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use azure functions, azure functions setup guide, azure functions vs aws lambda.

Ideal Agent Persona

Perfect for Cloud Agents needing serverless application development with Azure Functions

Core Value

Empowers agents to build event-driven computing applications using HTTP, timer, and queue triggers, and leverage durable functions for orchestration, all while utilizing Azure's serverless architecture and function binding capabilities

Capabilities Granted for azure-functions MCP Server

Automating workflows with Azure Function triggers
Building serverless APIs with HTTP triggers
Debugging and optimizing Azure Function performance

! Prerequisites & Limits

  • Requires Azure subscription and storage account
  • Limited to Azure Functions ecosystem
  • Dependent on Azure resource group and location
Project
SKILL.md
8.5 KB
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1.2 KB
package.json
240 B
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SKILL.md
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Azure Functions Skill

Build serverless applications with Azure Functions for event-driven computing.

Triggers

Use this skill when you see:

  • azure functions, function app, serverless azure
  • http trigger, timer trigger, queue trigger
  • durable functions, orchestration
  • function binding, function.json

Instructions

Create Function App

bash
1# Create storage account (required) 2az storage account create \ 3 --name myfuncstorage \ 4 --resource-group mygroup \ 5 --location eastus \ 6 --sku Standard_LRS 7 8# Create Function App 9az functionapp create \ 10 --name myfuncapp \ 11 --resource-group mygroup \ 12 --storage-account myfuncstorage \ 13 --consumption-plan-location eastus \ 14 --runtime python \ 15 --runtime-version 3.11 \ 16 --functions-version 4 17 18# Create with Premium plan 19az functionapp plan create \ 20 --name mypremiumplan \ 21 --resource-group mygroup \ 22 --location eastus \ 23 --sku EP1 24 25az functionapp create \ 26 --name myfuncapp \ 27 --resource-group mygroup \ 28 --storage-account myfuncstorage \ 29 --plan mypremiumplan \ 30 --runtime node \ 31 --runtime-version 20 \ 32 --functions-version 4

Python Functions (v2 Programming Model)

HTTP Trigger

python
1import azure.functions as func 2import logging 3import json 4 5app = func.FunctionApp(http_auth_level=func.AuthLevel.FUNCTION) 6 7@app.route(route="hello") 8def hello_http(req: func.HttpRequest) -> func.HttpResponse: 9 logging.info('HTTP trigger function processed a request.') 10 11 name = req.params.get('name') 12 if not name: 13 try: 14 req_body = req.get_json() 15 name = req_body.get('name') 16 except ValueError: 17 pass 18 19 if name: 20 return func.HttpResponse(f"Hello, {name}!") 21 else: 22 return func.HttpResponse( 23 "Please pass a name on the query string or in the request body", 24 status_code=400 25 ) 26 27@app.route(route="users/{id}", methods=["GET"]) 28def get_user(req: func.HttpRequest) -> func.HttpResponse: 29 user_id = req.route_params.get('id') 30 # Fetch user from database 31 return func.HttpResponse( 32 json.dumps({"id": user_id, "name": "John"}), 33 mimetype="application/json" 34 )

Timer Trigger

python
1@app.timer_trigger(schedule="0 */5 * * * *", arg_name="timer") 2def timer_function(timer: func.TimerRequest) -> None: 3 if timer.past_due: 4 logging.info('The timer is past due!') 5 6 logging.info('Timer trigger function executed.') 7 # Run scheduled task

Queue Trigger

python
1@app.queue_trigger(arg_name="msg", queue_name="myqueue", 2 connection="AzureWebJobsStorage") 3def queue_processor(msg: func.QueueMessage) -> None: 4 logging.info(f'Queue trigger processed: {msg.get_body().decode()}') 5 6 data = json.loads(msg.get_body().decode()) 7 process_message(data) 8 9# Output binding to queue 10@app.route(route="enqueue") 11@app.queue_output(arg_name="msg", queue_name="myqueue", 12 connection="AzureWebJobsStorage") 13def enqueue_message(req: func.HttpRequest, msg: func.Out[str]) -> func.HttpResponse: 14 message = req.get_json() 15 msg.set(json.dumps(message)) 16 return func.HttpResponse("Message enqueued", status_code=202)

Blob Trigger

python
1@app.blob_trigger(arg_name="blob", path="container/{name}", 2 connection="AzureWebJobsStorage") 3def blob_processor(blob: func.InputStream) -> None: 4 logging.info(f'Blob trigger: {blob.name}, Size: {blob.length} bytes') 5 content = blob.read() 6 process_blob(content) 7 8# Output binding to blob 9@app.route(route="upload") 10@app.blob_output(arg_name="outputblob", path="container/{rand-guid}.txt", 11 connection="AzureWebJobsStorage") 12def upload_blob(req: func.HttpRequest, outputblob: func.Out[str]) -> func.HttpResponse: 13 content = req.get_body().decode() 14 outputblob.set(content) 15 return func.HttpResponse("Blob created", status_code=201)

Cosmos DB Trigger

python
1@app.cosmos_db_trigger(arg_name="documents", 2 container_name="items", 3 database_name="mydb", 4 connection="CosmosDBConnection", 5 lease_container_name="leases", 6 create_lease_container_if_not_exists=True) 7def cosmos_trigger(documents: func.DocumentList) -> None: 8 for doc in documents: 9 logging.info(f'Document id: {doc["id"]}') 10 process_document(doc)

TypeScript Functions (v4 Programming Model)

typescript
1import { app, HttpRequest, HttpResponseInit, InvocationContext } from "@azure/functions"; 2 3// HTTP trigger 4app.http("hello", { 5 methods: ["GET", "POST"], 6 authLevel: "function", 7 handler: async (request: HttpRequest, context: InvocationContext): Promise<HttpResponseInit> => { 8 context.log(`Http function processed request for url "${request.url}"`); 9 10 const name = request.query.get("name") || (await request.text()) || "world"; 11 12 return { 13 body: `Hello, ${name}!`, 14 }; 15 }, 16}); 17 18// Timer trigger 19app.timer("timerTrigger", { 20 schedule: "0 */5 * * * *", 21 handler: async (timer: Timer, context: InvocationContext): Promise<void> => { 22 context.log("Timer trigger function executed"); 23 }, 24}); 25 26// Queue trigger with output binding 27app.storageQueue("queueTrigger", { 28 queueName: "myqueue", 29 connection: "AzureWebJobsStorage", 30 handler: async (message: unknown, context: InvocationContext): Promise<void> => { 31 context.log(`Queue message: ${JSON.stringify(message)}`); 32 }, 33});

Durable Functions

python
1import azure.functions as func 2import azure.durable_functions as df 3 4app = func.FunctionApp(http_auth_level=func.AuthLevel.FUNCTION) 5 6# Orchestrator 7@app.orchestration_trigger(context_name="context") 8def orchestrator(context: df.DurableOrchestrationContext): 9 # Fan-out/fan-in pattern 10 tasks = [] 11 for i in range(5): 12 tasks.append(context.call_activity("activity_function", i)) 13 14 results = yield context.task_all(tasks) 15 16 # Process results 17 total = sum(results) 18 return total 19 20# Activity 21@app.activity_trigger(input_name="input") 22def activity_function(input: int) -> int: 23 return input * 2 24 25# HTTP starter 26@app.route(route="orchestrators/{functionName}") 27@app.durable_client_input(client_name="client") 28async def http_start(req: func.HttpRequest, client: df.DurableOrchestrationClient) -> func.HttpResponse: 29 function_name = req.route_params.get('functionName') 30 instance_id = await client.start_new(function_name) 31 32 return client.create_check_status_response(req, instance_id)

Application Settings

bash
1# Set application settings 2az functionapp config appsettings set \ 3 --name myfuncapp \ 4 --resource-group mygroup \ 5 --settings "DatabaseConnection=connection-string" \ 6 "ApiKey=your-api-key" 7 8# Get application settings 9az functionapp config appsettings list \ 10 --name myfuncapp \ 11 --resource-group mygroup 12 13# Reference Key Vault secrets 14az functionapp config appsettings set \ 15 --name myfuncapp \ 16 --resource-group mygroup \ 17 --settings "Secret=@Microsoft.KeyVault(SecretUri=https://myvault.vault.azure.net/secrets/mysecret/)"

Managed Identity

python
1from azure.identity import DefaultAzureCredential 2from azure.keyvault.secrets import SecretClient 3 4# Use managed identity 5credential = DefaultAzureCredential() 6secret_client = SecretClient( 7 vault_url="https://myvault.vault.azure.net", 8 credential=credential 9) 10 11secret = secret_client.get_secret("my-secret")

Deployment

bash
1# Deploy from local 2func azure functionapp publish myfuncapp 3 4# Deploy with zip 5az functionapp deployment source config-zip \ 6 --name myfuncapp \ 7 --resource-group mygroup \ 8 --src app.zip 9 10# Continuous deployment from GitHub 11az functionapp deployment source config \ 12 --name myfuncapp \ 13 --resource-group mygroup \ 14 --repo-url https://github.com/org/repo \ 15 --branch main \ 16 --manual-integration

Best Practices

  1. Cold Starts: Use Premium plan for latency-sensitive apps
  2. Bindings: Use input/output bindings instead of SDK calls when possible
  3. Secrets: Use Key Vault references for sensitive settings
  4. Logging: Use structured logging with Application Insights
  5. Scaling: Configure host.json for optimal scaling

Common Workflows

API Backend

  1. Create Function App with HTTP triggers
  2. Implement CRUD operations
  3. Add authentication (Azure AD, API keys)
  4. Configure CORS settings
  5. Enable Application Insights

Event Processing

  1. Set up queue/blob/Cosmos DB triggers
  2. Implement processing logic
  3. Configure dead-letter queues
  4. Add retry policies
  5. Monitor with alerts

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