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Adding Initial MCP Tool Example
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‎src/.funcignore‎

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.venv

‎src/.gitignore‎

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bin
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obj
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csx
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.vs
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edge
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Publish
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*.user
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*.suo
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*.cscfg
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*.Cache
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project.lock.json
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/packages
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/TestResults
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/tools/NuGet.exe
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/App_Data
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/secrets
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/data
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.secrets
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appsettings.json
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local.settings.json
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node_modules
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dist
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# Local python packages
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.python_packages/
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# Python Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# Azurite artifacts
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__blobstorage__
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__queuestorage__
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__azurite_db*__.json

‎src/.vscode/extensions.json‎

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{
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"recommendations": [
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"ms-azuretools.vscode-azurefunctions",
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"ms-python.python"
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]
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}

‎src/.vscode/launch.json‎

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{
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"version": "0.2.0",
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"configurations": [
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{
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"name": "Attach to Python Functions",
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"type": "debugpy",
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"request": "attach",
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"connect": {
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"host": "localhost",
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"port": 9091
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},
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"preLaunchTask": "func: host start"
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}
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]
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}

‎src/.vscode/settings.json‎

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{
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"files.exclude": {
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"obj": true,
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"bin": true
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},
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"azureFunctions.deploySubpath": ".",
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"azureFunctions.scmDoBuildDuringDeployment": true,
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"azureFunctions.pythonVenv": ".venv",
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"azureFunctions.projectLanguage": "Python",
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"azureFunctions.projectRuntime": "~4",
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"debug.internalConsoleOptions": "neverOpen",
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"azureFunctions.projectLanguageModel": 2,
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"azureFunctions.preDeployTask": "func: extensions install"
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}

‎src/.vscode/tasks.json‎

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{
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"version": "2.0.0",
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"tasks": [
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{
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"label": "pip install (functions)",
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"type": "shell",
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"osx": {
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"command": "${config:azureFunctions.pythonVenv}/bin/python -m pip install -r requirements.txt"
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},
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"windows": {
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"command": "${config:azureFunctions.pythonVenv}\\Scripts\\python -m pip install -r requirements.txt"
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},
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"linux": {
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"command": "${config:azureFunctions.pythonVenv}/bin/python -m pip install -r requirements.txt"
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},
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"problemMatcher": []
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},
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{
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"type": "func",
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"label": "func: host start",
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"command": "host start",
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"problemMatcher": "$func-python-watch",
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"isBackground": true,
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"dependsOn": "func: extensions install"
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},
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{
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"type": "func",
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"command": "extensions install",
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"dependsOn": "pip install (functions)",
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"problemMatcher": []
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}
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]
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}

‎src/README.md‎

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# Python App with MCP Integration
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This guide walks you through setting up and connecting your Python application with the Model Context Protocol (MCP) Inspector.
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---
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## 📦 Installation & Setup
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### 1. Install Azure Functions Extensions
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Ensure you're inside your Python working directory and have the Azure Functions Core Tools installed. Then, run:
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```bash
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func extensions install
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```
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### 2. Activate Virtual Environment
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Make sure your Python virtual environment is activated before proceeding.
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```bash
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# Example (Linux/macOS)
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source venv/bin/activate
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# Example (Windows)
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.\venv\Scripts\activate
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```
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### 3. Start the Functions Host
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Run the following command to start the Azure Functions host:
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```bash
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func host start
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```
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## 🔗 Installation & Setup
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### 4. Start MCP Inspector
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Open a new terminal and run the MCP Inspector:
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```bash
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npx @modelcontextprotocol/inspector node build/index.js
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```
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### 5. Configure Connection
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Transport Type: SSE (Server-Sent Events)\
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URL: <http://0.0.0.0:7071/runtime/webhooks/mcp/sse>
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### 6. Connect to Server
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Click Connect within the MCP Inspector UI.
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## 🧰 Explore Tools
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Once generated:
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- You can list all generated tools
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- Select any tool to begin interacting with your Python function through MCP
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## ✅ Verification
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To verify the setup is working:
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- Confirm the MCP Inspector shows the connection is active
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- Tools appear in the inspector panel after connection
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- Selecting a tool returns the expected behavior or response

‎src/extensions.csproj‎

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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<TargetFramework>net8.0</TargetFramework>
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<WarningsAsErrors></WarningsAsErrors>
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<DefaultItemExcludes>**</DefaultItemExcludes>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Microsoft.Azure.Functions.Extensions.Mcp" Version="1.0.0-beta423" />
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<PackageReference Include="Microsoft.Azure.WebJobs.Extensions.Storage" Version="5.3.3" />
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<PackageReference Include="Microsoft.Azure.WebJobs.Script.ExtensionsMetadataGenerator" Version="1.1.3" />
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</ItemGroup>
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</Project>

‎src/function_app.py‎

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import azure.functions as func
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import logging
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import json
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app = func.FunctionApp(http_auth_level=func.AuthLevel.ANONYMOUS)
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# Constants for the Azure Blob Storage container and file name
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_CONTAINER_NAME = "test"
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_FILE_NAME = "test.txt"
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@app.generic_trigger(arg_name="context", type="mcpToolTrigger", toolName="hello",
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description="Gets code snippets from your snippet collection.",
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toolProperties="[]")
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def hello_mcp(context) -> None:
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"""
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A simple function that returns a greeting message.
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Args:
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context: The trigger context (not used in this function).
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Returns:
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str: A greeting message.
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"""
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return "Hello I am MCPTool!"
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@app.generic_trigger(arg_name="context", type="mcpToolTrigger", toolName="savesnippets",
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description="Save code snippets.",
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toolProperties="[{\"propertyName\":\"codeSnippet\",\"propertyType\":\"string\",\"description\":\"The name of the snippet.\"}]")
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@app.generic_output_binding(arg_name="file", type="blob", connection="AzureWebJobsStorage", path=f"{_CONTAINER_NAME}/{_FILE_NAME}")
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def save_snippets(context, file: func.Out[str]):
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"""
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Saves a code snippet to Azure Blob Storage.
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Args:
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context: The trigger context containing the input data as JSON.
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file (func.Out[str]): The output binding to write the snippet to Azure Blob Storage.
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Raises:
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KeyError: If the "codeSnippet" key is missing in the input JSON.
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json.JSONDecodeError: If the context is not valid JSON.
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"""
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content = json.loads(context)
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msg = content["arguments"]["codeSnippet"]
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logging.info(msg)
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file.set(msg) # Write the snippet to the specified blob
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@app.generic_trigger(arg_name="context", type="mcpToolTrigger", toolName="getsnippets",
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description="Gets code snippets from your snippet collection.",
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toolProperties="[]")
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@app.generic_input_binding(arg_name="file", type="blob", connection="AzureWebJobsStorage", path=f"{_CONTAINER_NAME}/{_FILE_NAME}")
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def get_snippets(file: func.InputStream, context) -> None:
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"""
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Retrieves a saved code snippet from Azure Blob Storage.
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Args:
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file (func.InputStream): The input binding to read the snippet from Azure Blob Storage.
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context: The trigger context (not used in this function).
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Returns:
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str: The content of the blob as a UTF-8 decoded string.
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Raises:
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Exception: If the blob does not exist or cannot be read.
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"""
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return file.read().decode('utf-8') # Read and decode the blob content

‎src/host.json‎

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{
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"version": "2.0",
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"logging": {
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"applicationInsights": {
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"samplingSettings": {
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"isEnabled": true,
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"excludedTypes": "Request"
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}
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}
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}
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}

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