Discover Awesome MCP Servers

Quark Auto-Save MCP Server

Integrates with the quark-auto-save service to automate file saving from Quark Cloud Drive shares. It enables users to manage auto-save tasks, update configurations, and trigger immediate file transfers through natural language.

web-search-agent

An MCP server that enables Claude Code to perform web searches via Bing, read webpage content, and get current time, with a smart search skill for structured multi-source verification.

mcp-stdio-to-streamable-http-adapter

Bridges STDIO MCP clients to Streamable HTTP MCP servers, allowing any STDIO-supported client to use Streamable HTTP servers immediately.

travel-planner

Enables travel planning through natural language, providing weather forecasts, attraction search, itinerary generation, and distance calculations using free APIs.

Onde Inference MCP Server

Enables managing Onde Inference accounts and model catalog operations through MCP tools such as login, app management, model registration, and assignment. Returns structured JSON over stdio for use with any MCP client.

Gemini Code Context MCP

Provides persistent codebase context caching via Gemini API, enabling fast, cost-effective repeat queries for MCP hosts like Claude Code.

Argo Workflow MCP Server

Enables AI agents to manage Argo Workflows through REST API, supporting workflow template and instance operations including creation, submission, monitoring, and deletion with token authentication.

Azure Model Context Protocol (MCP) Hub

Okay, here are some resources, tools, and sample code links that can help you build and integrate Model Context Protocol (MCP) servers on Azure using multiple languages. Keep in mind that MCP is relatively new, so the ecosystem is still developing. I'll focus on providing general Azure integration guidance that can be adapted to MCP. **Understanding Model Context Protocol (MCP)** * **MCP Specification (Important):** The official MCP specification is the most important resource. You'll need to understand the protocol details to implement a server. Look for the latest version on the relevant standards body website or the project's GitHub repository (if it's open source). Unfortunately, I can't provide a direct link without knowing the specific organization behind MCP. Search for "Model Context Protocol specification" to find it. **General Azure Integration Resources (Language Agnostic)** These resources are useful regardless of the programming language you choose. * **Azure App Service:** A common way to host web applications (including MCP servers) on Azure. * **Documentation:** [https://learn.microsoft.com/en-us/azure/app-service/](https://learn.microsoft.com/en-us/azure/app-service/) * **Quickstarts (Multiple Languages):** Azure App Service has quickstarts for various languages like Python, Node.js, .NET, Java, and PHP. These will help you deploy a basic web app, which you can then adapt to handle MCP requests. Look for the "Web App" quickstarts. * **Azure Functions:** A serverless compute service that can be triggered by HTTP requests (ideal for simple MCP endpoints). * **Documentation:** [https://learn.microsoft.com/en-us/azure/azure-functions/](https://learn.microsoft.com/en-us/azure/azure-functions/) * **Quickstarts (Multiple Languages):** Similar to App Service, Azure Functions has quickstarts for many languages. Focus on the "HTTP trigger" function type. * **Azure API Management (APIM):** Useful for managing, securing, and monitoring your MCP server endpoints. You can put APIM in front of your App Service or Azure Functions. * **Documentation:** [https://learn.microsoft.com/en-us/azure/api-management/](https://learn.microsoft.com/en-us/azure/api-management/) * **Azure Container Apps:** A serverless container execution environment. Useful if you want to package your MCP server in a Docker container. * **Documentation:** [https://learn.microsoft.com/en-us/azure/container-apps/](https://learn.microsoft.com/en-us/azure/container-apps/) **Language-Specific Resources and Examples** Here are some examples of how you might implement an MCP server in different languages on Azure. These are *general* examples of building web APIs; you'll need to adapt them to the specifics of the MCP protocol. * **Python:** * **Frameworks:** Flask or FastAPI are popular choices for building web APIs in Python. * **Azure App Service Quickstart (Python):** [https://learn.microsoft.com/en-us/azure/app-service/quickstart-python](https://learn.microsoft.com/en-us/azure/app-service/quickstart-python) * **Azure Functions Quickstart (Python):** [https://learn.microsoft.com/en-us/azure/azure-functions/create-first-function-python](https://learn.microsoft.com/en-us/azure/azure-functions/create-first-function-python) * **Example (Flask):** A simple Flask app that receives a POST request and returns a response (adapt this to MCP): ```python from flask import Flask, request, jsonify app = Flask(__name__) @app.route('/mcp_endpoint', methods=['POST']) def mcp_handler(): data = request.get_json() # Get the JSON data from the request # Process the data according to the MCP specification # ... your MCP logic here ... response_data = {"status": "success", "message": "MCP request processed"} return jsonify(response_data), 200 if __name__ == '__main__': app.run(debug=True) ``` * **.NET (C#):** * **Framework:** ASP.NET Core is the standard for building web APIs in .NET. * **Azure App Service Quickstart (.NET):** [https://learn.microsoft.com/en-us/azure/app-service/quickstart-dotnetcore](https://learn.microsoft.com/en-us/azure/app-service/quickstart-dotnetcore) * **Azure Functions Quickstart (.NET):** [https://learn.microsoft.com/en-us/azure/azure-functions/create-first-function-vs](https://learn.microsoft.com/en-us/azure/azure-functions/create-first-function-vs) * **Example (ASP.NET Core):** ```csharp using Microsoft.AspNetCore.Mvc; namespace MyMcpApp.Controllers { [ApiController] [Route("[controller]")] public class McpController : ControllerBase { [HttpPost] public IActionResult HandleMcpRequest([FromBody] object requestData) // Replace object with your MCP request model { // Process the requestData according to the MCP specification // ... your MCP logic here ... return Ok(new { Status = "success", Message = "MCP request processed" }); } } } ``` * **Node.js (JavaScript/TypeScript):** * **Frameworks:** Express.js is a popular choice. * **Azure App Service Quickstart (Node.js):** [https://learn.microsoft.com/en-us/azure/app-service/quickstart-nodejs](https://learn.microsoft.com/en-us/azure/app-service/quickstart-nodejs) * **Azure Functions Quickstart (Node.js):** [https://learn.microsoft.com/en-us/azure/azure-functions/create-first-function-node](https://learn.microsoft.com/en-us/azure/azure-functions/create-first-function-node) * **Example (Express.js):** ```javascript const express = require('express'); const app = express(); const port = 3000; app.use(express.json()); // for parsing application/json app.post('/mcp_endpoint', (req, res) => { const data = req.body; // Process the data according to the MCP specification // ... your MCP logic here ... res.json({ status: 'success', message: 'MCP request processed' }); }); app.listen(port, () => { console.log(`MCP server listening at http://localhost:${port}`); }); ``` * **Java:** * **Frameworks:** Spring Boot is a common choice for building web APIs in Java. * **Azure App Service Quickstart (Java):** [https://learn.microsoft.com/en-us/azure/app-service/quickstart-java](https://learn.microsoft.com/en-us/azure/app-service/quickstart-java) * **Azure Functions Quickstart (Java):** [https://learn.microsoft.com/en-us/azure/azure-functions/create-first-java-function](https://learn.microsoft.com/en-us/azure/azure-functions/create-first-java-function) * **Example (Spring Boot):** ```java import org.springframework.web.bind.annotation.PostMapping; import org.springframework.web.bind.annotation.RequestBody; import org.springframework.web.bind.annotation.RestController; @RestController public class McpController { @PostMapping("/mcp_endpoint") public Object handleMcpRequest(@RequestBody Object requestData) { // Replace Object with your MCP request model // Process the requestData according to the MCP specification // ... your MCP logic here ... return new Object() { public String status = "success"; public String message = "MCP request processed"; }; } } ``` **Key Considerations for MCP Implementation** * **Data Serialization/Deserialization:** MCP likely defines a specific data format (e.g., JSON, Protocol Buffers). Make sure your server correctly serializes and deserializes data according to the MCP specification. Use appropriate libraries for your chosen language. * **Error Handling:** Implement robust error handling to gracefully handle invalid requests or processing errors. Return appropriate error codes and messages as defined by the MCP specification. * **Security:** Secure your MCP endpoints using HTTPS and appropriate authentication/authorization mechanisms. Consider using Azure Active Directory (Azure AD) for authentication. * **Monitoring and Logging:** Use Azure Monitor to monitor the performance and health of your MCP server. Implement logging to track requests, errors, and other relevant information. * **Scalability:** Design your MCP server to be scalable to handle increasing traffic. Consider using Azure's scaling features (e.g., auto-scaling in App Service or Azure Functions). **Steps to Build and Integrate an MCP Server on Azure** 1. **Understand the MCP Specification:** Thoroughly review the MCP specification to understand the required data formats, endpoints, and error handling. 2. **Choose a Language and Framework:** Select a programming language and web framework that you are comfortable with and that are well-supported on Azure. 3. **Implement the MCP Server Logic:** Write the code to handle MCP requests, process the data, and return appropriate responses according to the MCP specification. 4. **Test Locally:** Thoroughly test your MCP server locally before deploying it to Azure. 5. **Deploy to Azure:** Choose an Azure hosting option (App Service, Azure Functions, Container Apps) and deploy your MCP server. 6. **Configure API Management (Optional):** If you need to manage, secure, or monitor your MCP endpoints, configure Azure API Management. 7. **Monitor and Maintain:** Monitor the performance and health of your MCP server using Azure Monitor and make any necessary adjustments. **Important Notes:** * **MCP-Specific Libraries:** Check if there are any existing libraries or SDKs for your chosen language that simplify the implementation of the MCP protocol. Search on GitHub or package repositories (e.g., PyPI for Python, NuGet for .NET, npm for Node.js). * **Official MCP Documentation:** The official MCP documentation is the *most* important resource. Refer to it for the definitive details of the protocol. I hope this comprehensive guide helps you build and integrate your MCP server on Azure! Good luck!

Cloudflare Image MCP

An MCP server for image generation and editing using Cloudflare Workers AI, providing OpenAI-compatible APIs and support for multiple models.

P-Link-MCP

Payment & Transaction Tools that allow AI agents to send, receive, and request payments

mcp-sofa

MCP server for Stack Overflow for Agents, enabling search, post creation, voting, and knowledge exchange for AI agents.

perplexity-mcp

Enables web search using Perplexity AI's API, allowing users to search the web with optional recency filters and integration with Claude, Cursor, and other MCP clients.

agentforge

MCP server that exposes 300+ AI agents as tools via a single API key. Supports listing agents, invoking any agent with chat-completion style messages, checking agent health, and retrieving platform statistics.

nexus

Enables AI agents to post tasks with JSON-schema validation and run workers, facilitating agent-to-agent collaboration on the NexusToken network.

SSW Workforce Intelligence MCP

Enables workforce and labor market analysis for Specified Skilled Workers in Japan by aggregating public census data to provide regional and industry insights, labor supply-demand gaps, competitive landscape, and wage trends.

Multimodal MCP

Enables semantic image search using CLIP embeddings and visual question answering through MCP tools, allowing natural language interaction with images.

Handwrytten MCP Server

Enables AI assistants to send real handwritten notes via physical cards using Handwrytten's robotic pen service, along with managing cards, addresses, and orders.

mcp-usaspending

Enables access to federal spending data from USAspending.gov API via Pipeworx MCP gateway.

persistenceone-bridgekitty

Cross-chain bridge aggregator MCP server for AI agents. Compares routes across LI.FI, deBridge, Relay, Across and Squid to find the best rate. Use when an agent needs to bridge or swap tokens between EVM chains, Solana, or Cosmos. The aggregator of aggregators.

mcp-horoscope

Horoscope MCP — wraps the keyless Horoscope App API.

mcp-malt

Enables access to the documented Malt API for back-office tasks, including retrieving invoices, payments, and commission invoices, as well as SCIM user provisioning for organization accounts.

ourgroceries-mcp

Manage grocery lists on OurGroceries.com via CLI or MCP, supporting item operations, list management, and natural-language resolution.

Tribunal TRF3: Certidão de Distribuição

MCP server for consulting distribution certificates from TRF3 (Tribunal Regional Federal da 3ª Região) via official source, providing read-only access with usage-based pricing.

ms-teams

Provides a standardized interface for interacting with Microsoft Teams tools and services through the Model Context Protocol.

mockscreenshots-mcp

Compose fake chat conversations and receive deep links to a pre-filled generator for preview, parody, and design mockups.

garmin-raw-mcp

Provides raw Garmin Connect data access for training analysis, enabling retrieval of activity summaries, lap data, time-series streams, comments with lactate, wellness metrics, and personal records through an MCP interface.

postlayer-connect

A local MCP server that enables AI assistants to post to social media platforms (LinkedIn, X, Bluesky, Mastodon, Reddit, etc.) using your own app credentials, with encrypted token storage and no middleman.

ClickHouse Cloud API MCP Server

A Multi-Agent Conversation Protocol server that enables interaction with the ClickHouse Cloud API, providing programmatic access to ClickHouse Cloud services through natural language.

Android Project MCP Server

Enables building, running unit tests, and instrumented tests for Android projects through the MCP protocol.