Discover Awesome MCP Servers

Primo MCP Server

MCP server for searching Ex Libris Primo library catalogues and subscribed databases, enabling search, record retrieval, autocomplete, citation generation, and export to BibTeX, RIS, or CSV.

TouchDesigner MCP Server

Enables natural language control of TouchDesigner via AI, allowing operator creation, parameter setting, Python execution, and node graph building.

ardhi-mcp

MCP server for Kenya land administration — title search, land rates, subdivision process, dispute resolution, land rights.

MySQL MCP Server Pro

Provides comprehensive MySQL database operations including CRUD, performance optimization, health analysis, and anomaly detection. Supports multiple connection modes, OAuth2.0 authentication, and role-based permissions for database management through natural language.

Playwright MCP Server

A minimal server that exposes Playwright browser automation capabilities through a simple API, enabling webpage interaction, DOM manipulation, and content extraction via the Model Context Protocol.

bubblyphone-agents

MCP server for BubblyPhone that lets AI assistants make real phone calls, manage AI voice agents, buy phone numbers in 30+ countries, and track billing. Supports 20 tools for full telephony control.

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.

skillfinder-mcp

An MCP server that provides on-demand skill discovery for AI coding agents by querying GitHub repositories, using BM25 search to return relevant SKILL.md content.

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.

resume-mcp

MCP server for maintaining a professional profile database and generating tailored, ATS-optimized resumes for specific job postings.

zotero-mcp-lite

A lightweight and customizable MCP server for Zotero that enables AI research tools to access and manage references through a simple API.

ollqd

Enables indexing and semantic search of codebases and documents via MCP, using Ollama embeddings and Qdrant vector store.

nima-career-mcp

Exposes Nima Karami's curated, public-safe career history. Allows AI to select and tailor pre-approved material for queries.

travel-planner

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

kaseya-vsa-mcp

MCP server for Kaseya VSA — endpoints, patches, procedures, alarms, and tickets. Enables AI assistants to manage and monitor devices via the Kaseya VSA RMM platform.

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 links to samples, tools, and resources that can help you build and integrate Model Context Protocol (MCP) servers on Azure using multiple languages. Keep in mind that MCP is a relatively new protocol, so direct, comprehensive resources might be limited. I'll focus on providing a combination of MCP-specific information and general Azure development resources that can be adapted. **Understanding Model Context Protocol (MCP)** * **MCP Specification (Microsoft Research):** This is the primary source for understanding the protocol itself. You'll need to understand the specification to implement a server. Look for the latest version on the Microsoft Research website or GitHub. Unfortunately, a direct link is difficult to provide as it may change. Search for "Model Context Protocol Specification" on your preferred search engine. * **MCP Blog Posts and Articles:** Search for blog posts and articles related to MCP. These can provide insights into use cases and implementation strategies. **General Azure Development Resources (Adaptable for MCP)** These resources are crucial because you'll likely be building your MCP server as an Azure service (e.g., Azure Function, Azure App Service, Azure Container Instance). * **Azure Documentation:** The official Azure documentation is your go-to resource. It covers everything from setting up your Azure account to deploying and managing your applications. Start here: [https://azure.microsoft.com/en-us/documentation/](https://azure.microsoft.com/en-us/documentation/) * **Azure SDKs:** Azure provides SDKs for various languages, making it easier to interact with Azure services. Here are links to the main SDKs: * **.NET (C#):** [https://github.com/Azure/azure-sdk-for-net](https://github.com/Azure/azure-sdk-for-net) * **Python:** [https://github.com/Azure/azure-sdk-for-python](https://github.com/Azure/azure-sdk-for-python) * **Java:** [https://github.com/Azure/azure-sdk-for-java](https://github.com/Azure/azure-sdk-for-java) * **Node.js (JavaScript/TypeScript):** [https://github.com/Azure/azure-sdk-for-js](https://github.com/Azure/azure-sdk-for-js) * **Go:** [https://github.com/Azure/azure-sdk-for-go](https://github.com/Azure/azure-sdk-for-go) * **Azure Samples:** Microsoft provides a vast library of code samples for Azure. Search for samples related to the specific Azure service you're using (e.g., "Azure Functions Python sample," "Azure App Service Java sample"). The Azure Samples GitHub repository is a good starting point: [https://github.com/Azure-Samples](https://github.com/Azure-Samples) * **Azure Functions:** A serverless compute service that allows you to run code without managing servers. It's a good option for building MCP servers. * **Azure Functions Documentation:** [https://docs.microsoft.com/en-us/azure/azure-functions/](https://docs.microsoft.com/en-us/azure/azure-functions/) * **Azure Functions Samples:** Search on GitHub for "Azure Functions samples" in your preferred language. * **Azure App Service:** A platform for building and deploying web applications. Another viable option for hosting your MCP server. * **Azure App Service Documentation:** [https://docs.microsoft.com/en-us/azure/app-service/](https://docs.microsoft.com/en-us/azure/app-service/) * **Azure App Service Samples:** Search on GitHub for "Azure App Service samples" in your preferred language. * **Azure Container Instances (ACI) / Azure Kubernetes Service (AKS):** If you're containerizing your MCP server, ACI or AKS are options. * **ACI Documentation:** [https://docs.microsoft.com/en-us/azure/container-instances/](https://docs.microsoft.com/en-us/azure/container-instances/) * **AKS Documentation:** [https://docs.microsoft.com/en-us/azure/aks/](https://docs.microsoft.com/en-us/azure/aks/) **Tools** * **Visual Studio Code (VS Code):** A popular code editor with excellent support for Azure development. It has extensions for various languages and Azure services. * **Azure CLI:** A command-line tool for managing Azure resources. * **Azure Portal:** The web-based interface for managing Azure resources. **Building an MCP Server on Azure (General Steps)** 1. **Choose a Language:** Select the programming language you're most comfortable with (e.g., Python, C#, Java, Node.js). 2. **Choose an Azure Service:** Decide whether to use Azure Functions, Azure App Service, ACI, or AKS to host your MCP server. Azure Functions is often a good starting point for simple implementations. 3. **Implement the MCP Protocol:** This is the core part. You'll need to: * **Parse MCP Requests:** Implement code to receive and parse incoming MCP requests according to the MCP specification. * **Process the Context:** Implement the logic to process the context information provided in the MCP request. This is where your model integration happens. * **Return MCP Responses:** Format and send back MCP responses according to the specification. 4. **Integrate with Azure Services:** Use the Azure SDK for your chosen language to interact with other Azure services if needed (e.g., Azure Storage, Azure Cognitive Services). 5. **Deploy to Azure:** Deploy your MCP server to your chosen Azure service. 6. **Test and Monitor:** Thoroughly test your MCP server and set up monitoring to ensure it's working correctly. **Example (Conceptual - Python with Azure Functions)** ```python # Example Azure Function (Python) - Very simplified import logging import azure.functions as func import json def main(req: func.HttpRequest) -> func.HttpResponse: logging.info('Python HTTP trigger function processed a request.') try: req_body = req.get_json() except ValueError: return func.HttpResponse( "Please pass a JSON payload in the request body", status_code=400 ) # **MCP Protocol Implementation (Simplified)** # In a real implementation, you would: # 1. Validate the request against the MCP specification. # 2. Extract the context information from the request. # 3. Process the context (e.g., use it to influence a model). # 4. Construct an MCP response. # For this example, we'll just echo back the request. response_data = { "status": "success", "received_context": req_body } return func.HttpResponse( json.dumps(response_data), mimetype="application/json", status_code=200 ) if __name__ == "__main__": # This is just for local testing. It won't run in Azure Functions. # You'd need to create a sample request and pass it to the main function. pass ``` **Important Considerations:** * **Security:** Implement proper authentication and authorization to protect your MCP server. Azure Active Directory (Azure AD) is a common choice. * **Scalability:** Design your MCP server to scale to handle the expected load. Azure Functions and App Service offer automatic scaling. * **Error Handling:** Implement robust error handling to gracefully handle unexpected situations. * **Logging and Monitoring:** Use Azure Monitor to log events and monitor the performance of your MCP server. **Key Takeaways:** * Start with the MCP specification to understand the protocol. * Use the Azure SDK for your chosen language to interact with Azure services. * Leverage Azure Functions or App Service for easy deployment and scaling. * Focus on security, error handling, and monitoring. Because MCP is relatively new, you might need to adapt existing Azure development patterns to fit the protocol's requirements. Good luck!

ClinicalTrials.gov MCP Server

Empowers AI agents with direct access to the official ClinicalTrials.gov database, enabling programmatic searching, retrieval, and analysis of clinical study data through a Model Context Protocol interface.

Docker Server Manager Go MCP

dockerServerManagerGoMCP

Pi-hole MCP Server

Enables management of Pi-hole DNS servers through natural language commands, including enabling/disabling blocking, viewing statistics, and configuration.

Vertica MCP Server

A Model Context Protocol server that enables AI assistants to interact with Vertica databases through SQL queries, schema inspection, database documentation, and data export capabilities.

@agenticbits/claude-plugin

Adds a live git branch status bar to the Claude interface for monitoring multiple repositories simultaneously. It provides tools for managing repository tracking and visibility through natural language commands.

Sonarr MCP Server

Enables AI assistants to manage TV series collections through Sonarr's API using natural language interactions. Supports searching, adding, updating, and deleting TV series with detailed control over quality profiles, season monitoring, and episode downloads.

MCP X++ Server

An MCP server for Microsoft Dynamics 365 Finance & Operations that enables the creation, modification, and analysis of D365 objects like classes, tables, and forms. It integrates with Visual Studio 2022 to provide tools for X++ code extraction, codebase search, and safe object deletion with dependency validation.

Word Live MCP Server

A Windows MCP server that attaches to a running Microsoft Word instance via COM automation and exposes 20 tools for reading, editing, formatting, and exporting documents — live on screen.

Apache Druid MCP Server

Enables querying and managing Apache Druid datasources through natural language, including SQL queries, datasource exploration, and cluster connectivity testing.

Zenith MCP Server

Personal habit tracking MCP server for a 90-day mission, tracking 6 non-negotiable habits with Supabase backend, exposes tools for logging and viewing progress.

MCP Server

A testing environment for Model Context Protocol that enables exploration of MCP capabilities and integration of AI models with external data sources and tools.