10 Microsoft MCP Servers to Accelerate Your Development Workflow

List of 10 Microsoft MCP Servers to Accelerate Your Development Workflow

1. Microsoft Learn Docs MCP Server

• What it does: Provides AI assistants with real-time access to official Microsoft documentation.
• Key Features: Semantic search across Microsoft Learn, Azure docs, and Microsoft 365 documentation.
• Real-world use: Accessing latest official documentation for technologies like C#, Azure, ASP.NET Core.
• Example Scenario: C# .NET Janitor chat mode for cleaning up and modernizing C# code.

2. Azure MCP Server

• What it does: Suite of 15+ specialized Azure service connectors for AI workflow.
• Key Modules: Database connectors, Azure Monitor, Resource Management, Authentication, Storage Services, Container Services.
• Real-world use: Managing Azure resources, log analysis, building Azure applications.
• Full demo scenario: Combining Azure MCP with GitHub Copilot for Azure extension in VS Code.

3. GitHub MCP Server

• What it does: Provides AI assistants with real-time access to GitHub repositories.
• Key Features: Creating, updating, and managing GitHub issues, pull requests, and repositories.
• Real-world use: Automating GitHub workflows, managing project tasks, collaborating on code.

4. Azure DevOps MCP Server

• What it does: Integrates AI assistants with Azure DevOps for project management.
• Key Features: Querying work items, creating pipelines, managing repositories, triggering builds.
• Real-world use: Streamlining development workflows, automating CI/CD processes, tracking project progress.

5. Docker MCP Server

• What it does: Connects AI assistants with Docker containers and images.
• Key Features: Pulling images, running containers, managing networks, volumes, and configurations.
• Real-world use: Building and deploying containerized applications, testing in isolated environments, automating Docker tasks.

6. Slack MCP Server

• What it does: Enables AI assistants to interact with Slack channels and messages.
• Key Features: Sending messages, notifications, managing channels, users, and permissions.
• Real-world use: Notifying team members about events, sharing updates, gathering feedback, facilitating communication.

7. Jira MCP Server

• What it does: Integrates AI assistants with Jira for project tracking and issue management.
• Key Features: Creating, updating, assigning, and transitioning Jira issues.
• Real-world use: Creating tickets from chat conversations, updating project statuses, monitoring issue progress.

8. MySQL MCP Server

• What it does: Provides AI assistants with real-time access to MySQL databases.
• Key Features: Querying databases, executing SQL commands, managing data, and schemas.
• Real-world use: Retrieving information from databases, updating records, executing SQL queries, managing database interactions.

9. Twitter MCP Server

• What it does: Enables AI assistants to interact with Twitter for social media engagement.
• Key Features: Sending tweets, direct messages, fetching timelines, managing followers.
• Real-world use: Sharing updates on Twitter, monitoring mentions, engaging with followers, analyzing trends.

10. AWS MCP Server

• What it does: Connects AI assistants with AWS services for cloud computing.
• Key Features: Managing AWS resources, querying cloud databases, deploying serverless functions.
• Real-world use: Automating AWS tasks, optimizing cloud infrastructure, integrating with AWS services.

These MCP servers can significantly enhance your development workflow by leveraging AI capabilities to streamline common tasks and improve productivity across various platforms and services.