MCP Builder
MicrosoftOfficialPublished by Microsoft
- Skill
- Guidelines
- Software development
- MIT
- Low risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
mcp-builder provides a structured, four-phase workflow for developing MCP servers that enable LLMs to interact with external services. It covers the entire lifecycle from initial research and planning, through implementation in TypeScript, Python, or C#, to testing and creating robust evaluations. The guide emphasizes best practices for tool design, schema definition, and error handling to ensure agents can effectively utilize the exposed functionality.
What it does
- Provides a step-by-step process for building MCP servers.
- Offers guidance on selecting the right language SDK (TypeScript, Python, C#).
- Defines standards for tool naming, schema design, and context management.
- Includes instructions for implementing core infrastructure like authentication and pagination.
- Outlines a methodology for creating XML-based evaluations to test agent performance.
- Provides references for Microsoft-specific MCP patterns and Azure integration.
When to use it
- When you need to integrate custom internal APIs or third-party SaaS into an LLM agent.
- When you are building a new MCP server and want to follow industry best practices.
- When you need to evaluate the effectiveness of your MCP server's tools.
- When deciding between building a custom server or using existing Microsoft MCP infrastructure.
Advantages
- Standardizes the development process for consistent, high-quality MCP servers.
- Promotes the use of structured schemas for better agent interaction.
- Includes a clear path for testing and validating server performance.
- Supports multiple programming languages and transport mechanisms.
Usage examples
- “I need to build an MCP server for my internal CRM API. What is the recommended workflow?”
- The agent will guide you through the four-phase process: planning your tool definitions, selecting the appropriate SDK, implementing the server with proper error handling, and creating an evaluation suite.
- “How should I structure my tool definitions for an MCP server?”
- The agent will provide patterns for clear, action-oriented naming, using Zod or Pydantic for input schemas, and defining output schemas to help agents process data effectively.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/mcp-builder/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip mcp-builder.zip -d .agents/skills
Documentation by Microsoft
MCP Server Development Guide
Overview
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
Microsoft MCP Ecosystem
Microsoft provides extensive MCP infrastructure for Azure and Foundry services. Understanding this ecosystem helps you decide whether to build custom servers or leverage existing ones.
Server Types
| Type | Transport | Use Case | Example |
|---|---|---|---|
| Local | stdio | Desktop apps, single-user, local dev | Azure MCP Server via NPM/Docker |
| Remote | Streamable HTTP | Cloud services, multi-tenant, Agent Service | https://mcp.ai.azure.com (Foundry) |
Microsoft MCP Servers
Before building a custom server, check if Microsoft already provides one:
| Server | Type | Description |
|---|---|---|
| Azure MCP | Local | 48+ Azure services (Storage, KeyVault, Cosmos, SQL, etc.) |
| Foundry MCP | Remote | https://mcp.ai.azure.com - Models, deployments, evals, agents |
| Fabric MCP | Local | Microsoft Fabric APIs, OneLake, item definitions |
| Playwright MCP | Local | Browser automation and testing |
| GitHub MCP | Remote | https://api.githubcopilot.com/mcp |
Full ecosystem: See 🔷 Microsoft MCP Patterns for complete server catalog and patterns.
When to Use Microsoft vs Custom
| Scenario | Recommendation |
|---|---|
| Azure service integration | Use Azure MCP Server (48 services covered) |
| AI Foundry agents/evals | Use Foundry MCP remote server |
| Custom internal APIs | Build custom server (this guide) |
| Third-party SaaS integration | Build custom server (this guide) |
| Extending Azure MCP | Follow Microsoft MCP Patterns |
Process
🚀 High-Level Workflow
Creating a high-quality MCP server involves four main phases:
Phase 1: Deep Research and Planning
1.1 Understand Modern MCP Design
API Coverage vs. Workflow Tools: Balance comprehensive API endpoint coverage with specialized workflow tools. Workflow tools can be more convenient for specific tasks, while comprehensive coverage gives agents flexibility to compose operations. Performance varies by client—some clients benefit from code execution that combines basic tools, while others work better with higher-level workflows. When uncertain, prioritize comprehensive API coverage.
Tool Naming and Discoverability:
Clear, descriptive tool names help agents find the right tools quickly. Use consistent prefixes (e.g., github_create_issue, github_list_repos) and action-oriented naming.
Context Management: Agents benefit from concise tool descriptions and the ability to filter/paginate results. Design tools that return focused, relevant data. Some clients support code execution which can help agents filter and process data efficiently.
Actionable Error Messages: Error messages should guide agents toward solutions with specific suggestions and next steps.
1.2 Study MCP Protocol Documentation
Navigate the MCP specification:
Start with the sitemap to find relevant pages: https://modelcontextprotocol.io/sitemap.xml
Then fetch specific pages with .md suffix for markdown format (e.g., https://modelcontextprotocol.io/specification/draft.md).
Key pages to review:
Specification overview and architecture
Transport mechanisms (streamable HTTP, stdio)
Tool, resource, and prompt definitions
1.3 Study Framework Documentation
Language Selection:
| Language | Best For | SDK |
|---|---|---|
| TypeScript (recommended) | General MCP servers, broad compatibility | @modelcontextprotocol/sdk |
| Python | Data/ML pipelines, FastAPI integration | mcp (FastMCP) |
| C#/.NET | Azure/Microsoft ecosystem, enterprise | Microsoft.Mcp.Core |
Transport Selection:
| Transport | Use Case | Characteristics |
|---|---|---|
| Streamable HTTP | Remote servers, multi-tenant, Agent Service | Stateless, scalable, requires auth |
| stdio | Local servers, desktop apps | Simple, single-user, no network |
Load framework documentation:
MCP Best Practices: 📋 View Best Practices - Core guidelines
For TypeScript (recommended):
TypeScript SDK: Use WebFetch to load
https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md⚡ TypeScript Guide - TypeScript patterns and examples
For Python:
Python SDK: Use WebFetch to load
https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md🐍 Python Guide - Python patterns and examples
For C#/.NET (Microsoft ecosystem):
🔷 Microsoft MCP Patterns - C# patterns, Azure MCP architecture, command hierarchy
1.4 Plan Your Implementation
Understand the API: Review the service's API documentation to identify key endpoints, authentication requirements, and data models. Use web search and WebFetch as needed.
Tool Selection: Prioritize comprehensive API coverage. List endpoints to implement, starting with the most common operations.
Phase 2: Implementation
2.1 Set Up Project Structure
See language-specific guides for project setup:
⚡ TypeScript Guide - Project structure, package.json, tsconfig.json
🐍 Python Guide - Module organization, dependencies
🔷 Microsoft MCP Patterns - C# project structure, command hierarchy
2.2 Implement Core Infrastructure
Create shared utilities:
API client with authentication
Error handling helpers
Response formatting (JSON/Markdown)
Pagination support
2.3 Implement Tools
For each tool:
Input Schema:
Use Zod (TypeScript) or Pydantic (Python)
Include constraints and clear descriptions
Add examples in field descriptions
Output Schema:
Define
outputSchemawhere possible for structured dataUse
structuredContentin tool responses (TypeScript SDK feature)Helps clients understand and process tool outputs
Tool Description:
Concise summary of functionality
Parameter descriptions
Return type schema
Implementation:
Async/await for I/O operations
Proper error handling with actionable messages
Support pagination where applicable
Return both text content and structured data when using modern SDKs
Annotations:
readOnlyHint: true/falsedestructiveHint: true/falseidempotentHint: true/falseopenWorldHint: true/false
Phase 3: Review and Test
3.1 Code Quality
Review for:
No duplicated code (DRY principle)
Consistent error handling
Full type coverage
Clear tool descriptions
3.2 Build and Test
TypeScript:
Run
npm run buildto verify compilationTest with MCP Inspector:
npx @modelcontextprotocol/inspector
Python:
Verify syntax:
python -m py_compile your_server.pyTest with MCP Inspector
See language-specific guides for detailed testing approaches and quality checklists.
Phase 4: Create Evaluations
After implementing your MCP server, create comprehensive evaluations to test its effectiveness.
Load ✅ Evaluation Guide for complete evaluation guidelines.
4.1 Understand Evaluation Purpose
Use evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions.
4.2 Create 10 Evaluation Questions
To create effective evaluations, follow the process outlined in the evaluation guide:
Tool Inspection: List available tools and understand their capabilities
Content Exploration: Use READ-ONLY operations to explore available data
Question Generation: Create 10 complex, realistic questions
Answer Verification: Solve each question yourself to verify answers
4.3 Evaluation Requirements
Ensure each question is:
Independent: Not dependent on other questions
Read-only: Only non-destructive operations required
Complex: Requiring multiple tool calls and deep exploration
Realistic: Based on real use cases humans would care about
Verifiable: Single, clear answer that can be verified by string comparison
Stable: Answer won't change over time
4.4 Output Format
Create an XML file with this structure:
<evaluation>
<qa_pair>
<question>Find discussions about AI model launches with animal codenames. One model needed a specific safety designation that uses the format ASL-X. What number X was being determined for the model named after a spotted wild cat?</question>
<answer>3</answer>
</qa_pair>
<!-- More qa_pairs... -->
</evaluation>Reference Files
📚 Documentation Library
Load these resources as needed during development:
Core MCP Documentation (Load First)
MCP Protocol: Start with sitemap at
https://modelcontextprotocol.io/sitemap.xml, then fetch specific pages with.mdsuffix📋 MCP Best Practices - Universal MCP guidelines including:
Server and tool naming conventions
Response format guidelines (JSON vs Markdown)
Pagination best practices
Transport selection (streamable HTTP vs stdio)
Security and error handling standards
Microsoft MCP Documentation (For Azure/Foundry)
🔷 Microsoft MCP Patterns - Microsoft-specific patterns including:
Azure MCP Server architecture (48+ Azure services)
C#/.NET command implementation patterns
Remote MCP with Foundry Agent Service
Authentication (Entra ID, OBO flow, Managed Identity)
Testing infrastructure with Bicep templates
SDK Documentation (Load During Phase 1/2)
Python SDK: Fetch from
https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.mdTypeScript SDK: Fetch from
https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.mdMicrosoft MCP SDK: See Microsoft MCP Patterns for C#/.NET
Language-Specific Implementation Guides (Load During Phase 2)
🐍 Python Implementation Guide - Complete Python/FastMCP guide with:
Server initialization patterns
Pydantic model examples
Tool registration with
@mcp.toolComplete working examples
Quality checklist
⚡ TypeScript Implementation Guide - Complete TypeScript guide with:
Project structure
Zod schema patterns
Tool registration with
server.registerToolComplete working examples
Quality checklist
🔷 Microsoft MCP Patterns - Complete C#/.NET guide with:
Command hierarchy (BaseCommand → GlobalCommand → SubscriptionCommand)
Naming conventions (
{Resource}{Operation}Command)Option handling with
.AsRequired()/.AsOptional()Azure Functions remote MCP deployment
Live test patterns with Bicep
Evaluation Guide (Load During Phase 4)
✅ Evaluation Guide - Complete evaluation creation guide with:
Question creation guidelines
Answer verification strategies
XML format specifications
Example questions and answers
Running an evaluation with the provided scripts
Files
- ATTRIBUTION.mdAdded by AutoGineer853 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md11.9 KiB
- reference/evaluation.md21.2 KiB
- reference/mcp_best_practices.md12.1 KiB
- reference/microsoft_mcp_patterns.md21.0 KiB
- reference/node_mcp_server.md28.5 KiB
- reference/python_mcp_server.md25.1 KiB
- scripts/connections.pyScript4.8 KiB
- scripts/evaluation.pyScript12.3 KiB
- scripts/example_evaluation.xml1.2 KiB
- scripts/requirements.txt29 B
reference/microsoft_mcp_patterns.md
Microsoft MCP Patterns
This document covers patterns from Microsoft's official MCP implementations, including the Azure MCP Server and Foundry MCP services. Use these patterns when building MCP servers that integrate with Azure services or follow Microsoft conventions.
Quick Reference
Microsoft MCP Ecosystem
| Server | Type | Transport | Description |
|---|---|---|---|
| Azure MCP | Local | stdio | 48+ Azure services (Storage, KeyVault, Cosmos, SQL, etc.) |
| Foundry MCP | Remote | Streamable HTTP | https://mcp.ai.azure.com - Models, deployments, evals, agents |
| Fabric MCP | Local | stdio | Microsoft Fabric APIs, OneLake, item definitions |
| Playwright MCP | Local | stdio | Browser automation and testing |
| GitHub MCP | Remote | Streamable HTTP | https://api.githubcopilot.com/mcp |
| Azure DevOps | Local | stdio | Pipelines, repos, boards |
| SQL Server | Local | stdio | SQL queries, schema (aka.ms/MssqlMcp) |
| Microsoft Learn | Remote | Streamable HTTP | https://learn.microsoft.com/api/mcp |
Distribution Formats
Install Azure MCP Server via your preferred method:
| Format | Package/Command | Best For |
|---|---|---|
| VS Code Extension | ms-azuretools.vscode-azure-mcp-server | VS Code users |
| NPM | npx @azure/mcp@latest | Node.js environments |
| .NET Tool | dotnet tool install -g Azure.Mcp | .NET developers |
| Docker | mcr.microsoft.com/azure-sdk/azure-mcp | Containers |
Command Naming Convention
azmcp <service> <resource> <operation>
Examples:
- azmcp storage blob list
- azmcp keyvault secret get
- azmcp cosmos document create
- azmcp appconfig kv setC# Command Class Naming
{Resource}{Operation}Command
Examples:
- StorageContainerListCommand
- KeyVaultSecretGetCommand
- CosmosDbDatabaseQueryCommandTool Metadata Annotations
| Annotation | Purpose | Example Use |
|---|---|---|
Destructive | Modifies or deletes resources | Delete operations |
ReadOnly | Only reads data, no side effects | List, get operations |
Idempotent | Safe to retry, same result | Create-or-update operations |
OpenWorld | Interacts with external systems | API calls to Azure |
Secret | Handles sensitive data | Key Vault operations |
LocalRequired | Requires local resources | File system operations |
Server Architecture
Azure MCP Service Coverage (48 Services)
| Category | Services |
|---|---|
| Compute | App Service, Functions, AKS, Container Registry, Virtual Desktop |
| Storage | Blob, File Shares, Cosmos DB, Redis, Managed Lustre |
| Data | SQL, PostgreSQL, MySQL, Data Explorer (Kusto), Confidential Ledger |
| AI/ML | AI Foundry, Search, Speech, Application Insights |
| Integration | Event Grid, Event Hubs, Service Bus, SignalR, Communication Services |
| Security | Key Vault, RBAC (Authorization), Policy, Advisor |
| Management | Monitor, Resource Health, Workbooks, Quota, Azure Migrate |
| DevOps | Load Testing, Grafana, Bicep Schema |
Full list: Storage, KeyVault, Cosmos, SQL, Postgres, MySQL, AKS, ACR, AppService, Functions, EventGrid, EventHubs, ServiceBus, SignalR, Search, Speech, Monitor, Advisor, Policy, Authorization, and 28+ more.
Server Modes
The Azure MCP Server supports multiple operational modes:
| Mode | Description | Use Case |
|---|---|---|
namespace | Default mode, tools organized by service namespace | General use |
consolidated | All tools in a single flat namespace | Simple integrations |
all | Exposes all available tools | Development/testing |
single | Single service only | Focused integrations |
Configuration Example (mcp.json)
{
"mcpServers": {
"azure": {
"command": "npx",
"args": ["-y", "@azure/mcp@latest", "server", "start"],
"env": {
"AZURE_TENANT_ID": "${AZURE_TENANT_ID}",
"AZURE_CLIENT_ID": "${AZURE_CLIENT_ID}"
}
}
}
}Server Manifest (server.json)
{
"name": "azure-mcp-server",
"version": "1.0.0",
"description": "MCP server for Azure services",
"capabilities": {
"tools": true,
"resources": false,
"prompts": false
},
"transports": ["stdio"],
"authentication": {
"type": "azure-identity",
"scopes": ["https://management.azure.com/.default"]
}
}Modular Architecture Pattern (C#/.NET)
Microsoft's Azure MCP Server uses a modular "Area" pattern for organizing tools by service domain.
Command Hierarchy
IBaseCommand
└── BaseCommand
└── GlobalCommand<TOptions> # No subscription required
└── SubscriptionCommand<TOptions> # Subscription context
└── Service-specific commands # Azure service operationsIAreaSetup Interface
Each Azure service implements IAreaSetup to register its tools:
public interface IAreaSetup
{
string Name { get; } // e.g., "storage", "keyvault"
string Title { get; } // e.g., "Azure Storage", "Azure Key Vault"
void ConfigureServices(IServiceCollection services);
void RegisterCommands(CommandGroup rootGroup);
}Implementation Example
public class StorageSetup : IAreaSetup
{
public string Name => "storage";
public string Title => "Azure Storage";
public void ConfigureServices(IServiceCollection services)
{
services.AddSingleton<BlobServiceClientFactory>();
services.AddSingleton<StorageAccountService>();
}
public void RegisterCommands(CommandGroup rootGroup)
{
var storageGroup = rootGroup.AddGroup("storage", "Azure Storage operations");
// Blob operations
var blobGroup = storageGroup.AddGroup("blob", "Blob storage operations");
blobGroup.AddCommand<ListBlobsCommand>("list", "List blobs in a container");
blobGroup.AddCommand<GetBlobCommand>("get", "Get blob content");
blobGroup.AddCommand<UploadBlobCommand>("upload", "Upload a blob");
blobGroup.AddCommand<DeleteBlobCommand>("delete", "Delete a blob");
// Container operations
var containerGroup = storageGroup.AddGroup("container", "Container operations");
containerGroup.AddCommand<ListContainersCommand>("list", "List containers");
containerGroup.AddCommand<CreateContainerCommand>("create", "Create a container");
}
}Command Implementation
public class ListBlobsCommand : ICommand
{
[Option("--account", "Storage account name")]
public string AccountName { get; set; } = string.Empty;
[Option("--container", "Container name")]
public string ContainerName { get; set; } = string.Empty;
[Option("--prefix", "Blob name prefix filter")]
public string? Prefix { get; set; }
[Option("--limit", "Maximum number of results")]
public int Limit { get; set; } = 100;
public ToolMetadata Metadata => new()
{
ReadOnly = true,
OpenWorld = true,
Idempotent = true
};
public async Task<CommandResponse> ExecuteAsync(
IServiceProvider services,
CancellationToken cancellationToken)
{
var factory = services.GetRequiredService<BlobServiceClientFactory>();
var client = factory.CreateClient(AccountName);
var container = client.GetBlobContainerClient(ContainerName);
var blobs = new List<BlobItem>();
await foreach (var blob in container.GetBlobsAsync(prefix: Prefix, cancellationToken: cancellationToken))
{
blobs.Add(blob);
if (blobs.Count >= Limit) break;
}
return CommandResponse.Success(new
{
account = AccountName,
container = ContainerName,
count = blobs.Count,
blobs = blobs.Select(b => new
{
name = b.Name,
size = b.Properties.ContentLength,
lastModified = b.Properties.LastModified,
contentType = b.Properties.ContentType
})
});
}
}Option Registration Extensions
// Required options
command.AddOption("--account")
.AsRequired()
.WithDescription("Storage account name");
// Optional options with defaults
command.AddOption("--limit")
.AsOptional()
.WithDefault(100)
.WithDescription("Maximum results to return");
// Enum options
command.AddOption("--access-tier")
.AsOptional()
.WithValues<AccessTier>()
.WithDescription("Blob access tier");Authentication Patterns
Azure Identity Credential Chain
Microsoft uses a credential chain that tries multiple authentication methods:
1. Environment Variables (AZURE_CLIENT_ID, AZURE_CLIENT_SECRET, AZURE_TENANT_ID)
2. Visual Studio credentials
3. Azure CLI credentials
4. Azure PowerShell credentials
5. Azure Developer CLI credentials
6. Interactive browser (development only)Environment Variable Controls
| Variable | Purpose |
|---|---|
AZURE_TOKEN_CREDENTIALS | Override credential type |
AZURE_TENANT_ID | Azure AD tenant ID |
AZURE_CLIENT_ID | Service principal client ID |
AZURE_CLIENT_SECRET | Service principal secret |
AZURE_SUBSCRIPTION_ID | Default subscription |
Credential Implementation
public class AzureCredentialProvider
{
public TokenCredential GetCredential()
{
var credentialType = Environment.GetEnvironmentVariable("AZURE_TOKEN_CREDENTIALS");
return credentialType?.ToLower() switch
{
"environment" => new EnvironmentCredential(),
"cli" => new AzureCliCredential(),
"managedidentity" => new ManagedIdentityCredential(),
_ => new DefaultAzureCredential(new DefaultAzureCredentialOptions
{
ExcludeInteractiveBrowserCredential = !IsDevelopment(),
ExcludeManagedIdentityCredential = IsDevelopment()
})
};
}
}Error Handling Patterns
Azure SDK Error Handling
public static CommandResponse HandleAzureError(RequestFailedException ex)
{
return ex.Status switch
{
404 => CommandResponse.Error(
$"Resource not found. Verify the resource exists and you have access. " +
$"Details: {ex.Message}"),
403 => CommandResponse.Error(
$"Access denied. Check your permissions and ensure your credentials " +
$"have the required role assignments. Details: {ex.Message}"),
401 => CommandResponse.Error(
$"Authentication failed. Run 'az login' or check your credentials. " +
$"Details: {ex.Message}"),
409 => CommandResponse.Error(
$"Conflict: Resource already exists or is in a conflicting state. " +
$"Details: {ex.Message}"),
429 => CommandResponse.Error(
$"Rate limit exceeded. Wait and retry. " +
$"Details: {ex.Message}"),
_ => CommandResponse.Error(
$"Azure API error (HTTP {ex.Status}): {ex.Message}")
};
}CommandResponse Pattern
public class CommandResponse
{
public bool IsSuccess { get; init; }
public object? Data { get; init; }
public string? Error { get; init; }
public static CommandResponse Success(object data) =>
new() { IsSuccess = true, Data = data };
public static CommandResponse Error(string message) =>
new() { IsSuccess = false, Error = message };
}Tool Metadata Best Practices
Annotation Guidelines
| Operation Type | Destructive | ReadOnly | Idempotent | OpenWorld |
|---|---|---|---|---|
| List/Get | ❌ | ✅ | ✅ | ✅ |
| Create | ❌ | ❌ | ❌ | ✅ |
| Create-or-Update | ❌ | ❌ | ✅ | ✅ |
| Update | ❌ | ❌ | ✅ | ✅ |
| Delete | ✅ | ❌ | ✅ | ✅ |
| Purge (permanent) | ✅ | ❌ | ❌ | ✅ |
Metadata Implementation
public class ToolMetadata
{
/// <summary>
/// Tool may perform destructive operations (delete, purge).
/// Clients should confirm before execution.
/// </summary>
public bool Destructive { get; init; }
/// <summary>
/// Tool only reads data, no side effects.
/// Safe to call without confirmation.
/// </summary>
public bool ReadOnly { get; init; }
/// <summary>
/// Repeated calls with same arguments produce same result.
/// Safe to retry on failure.
/// </summary>
public bool Idempotent { get; init; }
/// <summary>
/// Tool interacts with external systems (Azure APIs).
/// May have latency or availability concerns.
/// </summary>
public bool OpenWorld { get; init; }
/// <summary>
/// Tool handles sensitive data (secrets, keys, credentials).
/// Output should be treated as confidential.
/// </summary>
public bool Secret { get; init; }
/// <summary>
/// Tool requires local resources (file system, environment).
/// May not work in all execution contexts.
/// </summary>
public bool LocalRequired { get; init; }
}Remote MCP with Azure Functions
Initialize from Template
# Python
azd init --template remote-mcp-functions-python -e mcpserver-python
# TypeScript
azd init --template remote-mcp-functions-typescript -e mcpserver-ts
# .NET
azd init --template remote-mcp-functions-dotnet -e mcpserver-dotnetTypeScript Tool Registration (Azure Functions)
import { app, InvocationContext } from '@azure/functions';
export async function mcpToolStorageList(
_toolArguments: unknown,
context: InvocationContext
): Promise<string> {
const args = context.triggerMetadata.mcptoolargs as {
accountName: string;
prefix?: string;
};
// Implementation
const containers = await listContainers(args.accountName, args.prefix);
return JSON.stringify(containers);
}
app.mcpTool('storage_container_list', {
toolName: 'storage_container_list',
description: 'List all containers in an Azure Storage account',
toolProperties: {
accountName: arg.string()
.describe('Storage account name')
.required(),
prefix: arg.string()
.describe('Filter containers by prefix')
.optional()
},
handler: mcpToolStorageList
});Deploy to Azure
# Deploy
azd up
# Get endpoint
# https://{function_app_name}.azurewebsites.net/runtime/webhooks/mcpTesting Infrastructure
Test Structure
tools/Azure.Mcp.Tools.{Service}/tests/
├── Azure.Mcp.Tools.{Service}.UnitTests/ # No Azure resources
├── Azure.Mcp.Tools.{Service}.LiveTests/ # Requires Azure
├── test-resources.bicep # Infrastructure template
└── test-resources-post.ps1 # Post-deployment setupUnit Tests (No Azure Resources)
[TestClass]
public class StorageContainerListCommandTests
{
[TestMethod]
public async Task ListContainers_ReturnsExpectedResults()
{
// Arrange
var mockClient = new Mock<BlobServiceClient>();
var command = new StorageContainerListCommand(mockClient.Object);
// Act
var result = await command.ExecuteAsync(new StorageContainerListOptions
{
AccountName = "teststorage"
});
// Assert
Assert.IsNotNull(result);
}
}Live Tests (Bicep Infrastructure)
// test-resources.bicep
param baseName string
param location string = resourceGroup().location
resource storageAccount 'Microsoft.Storage/storageAccounts@2023-01-01' = {
name: '${baseName}storage'
location: location
sku: { name: 'Standard_LRS' }
kind: 'StorageV2'
}
output STORAGE_ACCOUNT_NAME string = storageAccount.nameRunning Tests
# Unit tests only
./eng/scripts/Test-Code.ps1 -UnitTests
# Live tests (deploys Azure resources)
./eng/scripts/Test-Code.ps1 -LiveTests -ServiceDirectory Storage
# Deploy test resources manually
./eng/scripts/Deploy-TestResources.ps1 -ServiceDirectory StorageEngineering Standards
Code Style Requirements
| Rule | Requirement |
|---|---|
| Constructors | Use C# primary constructors |
| JSON | Use System.Text.Json (no Newtonsoft) |
| Classes | Make sealed when not inherited |
| Members | Make static when possible |
| Files | One class/interface per file |
| AOT | All code must be Native AOT compatible |
AOT Compatibility
// GOOD: AOT compatible
[JsonSerializable(typeof(ContainerListResponse))]
internal partial class ContainerJsonContext : JsonSerializerContext { }
// BAD: Reflection-based (not AOT safe)
JsonSerializer.Deserialize<ContainerListResponse>(json); // AvoidPR Checklist
Before submitting changes to Microsoft MCP:
[ ] Code builds with
dotnet build[ ] All unit tests pass
[ ] Live tests pass (if applicable)
[ ] AOT analysis passes:
./eng/scripts/Analyze-AOT-Compact.ps1[ ] Tool descriptions are clear and specific
[ ] No hardcoded credentials or endpoints
[ ] Follows naming conventions
Integration with Foundry Agent Service
MCP Tool Declaration (Python)
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import PromptAgentDefinition, MCPTool
mcp_tool = MCPTool(
server_label="azure-storage",
server_url="https://{app}.azurewebsites.net/runtime/webhooks/mcp",
require_approval="always",
allowed_tools=["storage_container_list"],
project_connection_id=connection_name
)
agent = project_client.agents.create_version(
agent_name="storage-agent",
definition=PromptAgentDefinition(
model="gpt-4o-mini",
instructions="Help users manage Azure Storage",
tools=[mcp_tool]
)
)MCP Tool Declaration (C#)
PromptAgentDefinition agentDefinition = new(model: "gpt-4o-mini")
{
Instructions = "Help users manage Azure Storage",
Tools = {
ResponseTool.CreateMcpTool(
serverLabel: "azure-storage",
serverUri: new Uri("https://{app}.azurewebsites.net/runtime/webhooks/mcp"),
toolCallApprovalPolicy: new McpToolCallApprovalPolicy(
GlobalMcpToolCallApprovalPolicy.AlwaysRequireApproval
)
)
}
};Handling Approval Requests
for item in response.output:
if item.type == "mcp_approval_request" and item.id:
print(f"Tool: {getattr(item, 'name', '<unknown>')}")
print(f"Arguments: {json.dumps(getattr(item, 'arguments', None), indent=2)}")
should_approve = input("Approve? (y/N): ").strip().lower() == "y"
input_list.append(McpApprovalResponse(
type="mcp_approval_response",
approve=should_approve,
approval_request_id=item.id
))When to Use Microsoft MCP vs Custom
Use Microsoft MCP Servers When:
✅ Integrating with Azure services (Storage, KeyVault, Cosmos, etc.)
✅ Working with AI Foundry (agents, evaluations, deployments)
✅ Need browser automation (Playwright MCP)
✅ GitHub integration (GitHub MCP)
✅ Microsoft Fabric operations
Build Custom MCP Servers When:
✅ Integrating with non-Microsoft services
✅ Custom internal APIs
✅ Third-party SaaS integrations
✅ Specialized domain logic not covered by existing servers
✅ Need to extend Azure MCP with custom tools
Extending Azure MCP
If you need to add custom tools alongside Azure MCP:
Separate Server: Create a custom MCP server for your tools
Multi-Server Config: Configure both servers in mcp.json
Namespace Prefix: Use distinct prefixes to avoid conflicts
{
"mcpServers": {
"azure": {
"command": "npx",
"args": ["-y", "@azure/mcp@latest", "server", "start"]
},
"custom": {
"command": "node",
"args": ["./dist/custom-mcp-server.js"]
}
}
}Resources
Azure MCP Server: github.com/microsoft/mcp
MCP Protocol Spec: modelcontextprotocol.io
Azure Identity: Azure SDK Authentication
Foundry Documentation: AI Foundry Docs
Azure MCP Server Docs: learn.microsoft.com/azure/developer/azure-mcp-server
AZD MCP Templates: azure.github.io/awesome-azd/?tags=mcp
Code Samples
| Sample | Description | Language |
|---|---|---|
remote-mcp-apim-functions-python | Secure remote MCP with API Management | Python |
remote-mcp-functions-python | Basic Azure Functions MCP | Python |
remote-mcp-functions-dotnet | Azure Functions MCP | C# |
remote-mcp-functions-typescript | Azure Functions MCP | TypeScript |
mcp-container-ts | MCP on Azure Container Apps | TypeScript |
Requirements and compatibility
Written for: Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Names Claude Code tools, Needs an MCP server, Needs network access, Needs Python, Needs Node.js
Security
What our scanner noticed· Low risk
- Instructions that use the network
- Scripts that your agent may run
This skill includes scripts that your agent may run. Read them before you use it.
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Microsoft
- Publisher
- Microsoft (Official)
- Source
- microsoft/skills · .github/skills/mcp-builder · commit 0696600
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Microsoft.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download mcp-builder.zip