Microsoft Model Context Protocol (MCP) Servers

This repository catalogs various Microsoft implementations of the Model Context Protocol (MCP), an open standard that facilitates seamless integration between AI applications and external data sources and tools. MCP enables AI models to access the context they need to perform tasks effectively.

📘 What is MCP?

Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to large language models (LLMs). It allows AI applications to connect with various data sources and tools in a consistent manner, enhancing their capabilities and flexibility. MCP follows a client-server architecture where:

MCP Hosts: Applications like AI assistants or integrated development environments (IDEs) that initiate connections.
MCP Clients: Connectors within the host application that maintain 1:1 connections with servers.
MCP Servers: Services that provide context and capabilities through the standardized MCP.

For more details, visit the official MCP website.

📂 Microsoft MCP Servers

Below are Microsoft's official MCP server implementations:

🔷 Azure MCP Server

Repository: azure/azure-mcp
Description: Implements the MCP standard to manage Azure resources, enabling declarative provisioning and integration with AI workflows.

Dataverse MCP Server

Documentation: Microsoft Dataverse
Description: Chat over your business data using NL - Discover tables, run queries, retrieve data, insert or update records, and execute custom prompts grounded in business knowledge and context.

🎭 Playwright MCP

Repository: microsoft/playwright-mcp
Description: An MCP server for browsing the internet. Enables LLMs to interact with web pages through structured accessibility snapshots. Useful for web navigation and form-filling, data extraction from structured content, automated testing driven by LLMs, and general-purpose browser interaction for agents.

📁 Files MCP Server

Repository: microsoft/files-mcp-server
Description: Provides a declarative control plane for managing file-based resources, supporting AI workflows that involve static files and documentation synchronization.

📝 Markitdown MCP Server

Repository: microsoft/markitdown
Description: A specialized MCP server for Markdown processing and manipulation. Enables AI models to read, write, and transform Markdown content with robust parsing and formatting capabilities.

📊 Clarity MCP Server

Repository: @microsoft/clarity-mcp-server
Description: An MCP server for Microsoft Clarity analytics integration. Enables AI models to access web analytics data, heatmaps, and session recordings to understand user behavior and site performance.

📚 Microsoft Docs MCP Server

Repository: microsoftdocs/mcp
Description: An MCP server that provides structured access to Microsoft’s official documentation. Enables AI models to retrieve accurate, authoritative, and context-aware technical content for code generation, question answering, and workflow grounding.

🛢️Microsoft SQL MCP Server

Repository: MSSQL MCP Server
Description: Chat with your business data the new agentic way using natural language and AI. Connect to any SQL database—from ground (on-premises) to Azure cloud to Microsoft Fabric via a simple connection string. Discover and define table schemas, manage tables, and perform CRUD operations through conversational prompts.

🛢️Microsoft Fabric Real-Time Intelligence MCP Server

Repository: RTI MCP Server
Description: Chat with your real-time data the new agentic way using natural language and AI. MCP server for Fabric Real-Time Intelligence supporting tools for Eventhouse, Azure Data Explorer, and other RTI services (coming soon)

📅 Azure DevOps MCP Server

Repository: Azure DevOps MCP Server - Public Preview
Description: The MCP Server for Azure DevOps enables you to bring context into AI workflows and interact with Azure DevOps artifacts such as work items, test plans, builds, releases, and pull requests.

📎 Related Resources

🏗️ Templates

Looking for starter templates that use MCP? Check out the Azure Developer CLI (azd) templates tagged with MCP.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

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