What is MCP?
Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to LLMs, defined by Anthropic.
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A lab that demonstrates how to deploy an MCP server on Azure and add it as an action in Microsoft Copilot Studio. It uses the Model Context Protocol (MCP) to connect AI models to data sources and tools, allowing makers to integrate knowledge servers and APIs directly into Copilot Studio.
Follow the lab steps: create a GitHub repository from the template, deploy an Azure Web App, create a Power Platform connector, and add the MCP server as an action in Copilot Studio. Specific actions include setting up the web app with Node 22 LTS, configuring the connector via Swagger editor, and enabling generative AI orchestration.
Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to LLMs, defined by Anthropic.
MCP servers use connector infrastructure, so they are better together. MCP enables real-time data access while employing enterprise governance features like Virtual Network and Data Loss Prevention.
You need an Azure Subscription, a GitHub account, a Copilot Studio trial or developer account, and a Power Platform environment.
The server runs as an Azure Web App and is publicly available. The lab warns users to delete the web app after finishing. Enterprise governance controls are supported through the connector infrastructure.
Copilot Studio currently supports only Tools via MCP. Known issues and planned improvements are detailed at [aka.ms/mcsmcp](https://aka.ms/mcsmcp).
TestMu AI MCP Server lets developers run, debug, and triage tests through natural language directly from their IDE (Cursor, Claude, GitHub Copilot, and other MCP clients). It exposes five tools — HyperExecute (test orche
Modelglass turns "which model should I use?" into a lookup instead of a guess. Seven tools give your agent live pricing across image, language, video, and audio models. Sourced and versioned, not scraped once and forgott
OrangePro local-first CLI + MCP server for behavior mapping, grounded test generation, and dynamic proof.

Verified distributed compute for humans, applications, and agents. Submit Blender, Octane, and video workloads, route them across qualified GPUs, track asynchronous execution, download finished artifacts, and verify FARP

ArtiBot Cloud MCP (Zhijiangyun 智匠云) — cloud MCP server for robot manipulation data & GPU workloads. 15 tools: robot fleet management, data collection & video recording, post-processing pipelines, and benchmark evaluation
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