Azure Model Context Protocol (MCP) Hub
LocalAbout Azure Model Context Protocol (MCP) Hub
Azure Model Context Protocol (MCP) Hub is a resource index of samples, tools and links for building and integrating MCP servers on Azure. It targets developers working in C#, Python, Java or JavaScript who build AI agents. The page also lists community-maintained MCP servers that agents can call directly.
Key features
- 01Hosting MCP servers on Azure Functions
- 02Official MCP SDKs listed for several languages
- 03Integration examples for common AI SDKs and frameworks
- 04Listed ready-made MCP servers for data services
- 05Listed ready-made MCP servers for DevOps and infrastructure
Use cases
- 01Deploying a self-built MCP server on Azure
- 02Finding prebuilt MCP servers for databases or DevOps tasks
- 03Reviewing how MCP fits into Azure AI frameworks
MCP support
This project is a resource index that lists SDKs for building MCP servers and clients, along with ready-made MCP servers such as Redis, PostgreSQL, MySQL, Azure CLI and Kubernetes.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEAzure Model Context Protocol (MCP) Hub
Build AI agents that call real APIs — fast. Whether you're a C#, Python, Java, or JavaScript developer, this hub helps you build, run, or reuse Model Context Protocol (MCP) servers on Azure to power your AI agents.
🚀 1. Run Your Own MCP Server
Host your own MCP server using Azure Functions — pick your language:
🧠 2. Build Agents That Use MCP
Use official SDKs or your favorite AI frameworks to write agents that connect to any MCP server.
✅ Official MCP SDKs (Build Clients, Servers, or Tools in Any Language)
🤖 AI SDK Integrations
- Python: OpenAI Agents SDK — Use MCPServerSse with Azure OpenAI
- C#: Semantic Kernel — Add MCP tools to your Kernel instance
- JavaScript: LangChain.js — Use MCP tools in LangChain or LangGraph agents
- Java: Spring AI — Plug into Spring Boot with auto-config
- Azure AI Agents — Add Bing + Azure AI Search to your agent
🧩 3. Use Plug-and-Play MCP Servers
Don't want to build your own tools? These servers expose real APIs via MCP so your agents can just call them.
⚠️ These servers are open source and maintained by the community. Microsoft does not review, support, or endorse them. Use at your own discretion.
🗃️ Data APIs
- Redis — Access Azure Redis
- PostgreSQL — Query Azure PostgreSQL
- MySQL — Use with Azure MySQL
- MongoDB — Talk to Cosmos DB with MongoDB
- Azure Data Explorer (ADX) — Run KQL queries via agent
🔧 Dev & Infra APIs
- Azure CLI — Run CLI commands with natural language
- Kubernetes — Control AKS clusters
- GitHub — Access GitHub APIs via chat or agent
- Azure DevOps (Python) — Work item support
- Azure DevOps (Node.js) — Repos, pipelines, and boards
📚 Learn More
- 📄 Model Context Protocol Spec
- 🧪 Explore sample agents, tools, and servers in the linked repos
- 🤝 Contribute a new server or tool via PR!
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.