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Kevin McDonnell and Garry Trinder delve into the world of Model Context Protocol (MCP) and its implications for developers. We start with a starter overview of functionality of MCP and why it is important. However, we wanted to get beyond that initial view that is covered elsewhere and look at some of the challenges associated with using MCP and broader considerations that you need to be looking at. The conversation covers the importance of optimizing documentation for language models, governance in MCP usage, and strategies for getting started with MCP and then scaling.
Takeaways
Useful links
Introduction - Model Context Protocol
Getting started with Local MCP Servers on Claude Desktop | Anthropic Help Center and For Claude Desktop Users – Model Context Protocol (MCP)
Use MCP servers in VS Code
Community built Graph MCP Server - GitHub - merill/lokka: MCP (Model Context Protocol) for Microsoft 365.
Azure AI Search:
Full text search - Azure AI Search | Microsoft Learn
Vector search - Azure AI Search | Microsoft Learn
Hybrid search - Azure AI Search | Microsoft Learn
MCP for beginners course - GitHub - microsoft/mcp-for-beginners
MCP Dev Days 29th/30th July (and available on demand after) - MCP Dev Days | Microsoft Reactor
Microsoft MCP Lab - GitHub - microsoft/mcsmcp: Lab for creating an MCP Server and using it in Microsoft Copilot Studio.
Microsoft's MCP Server collection - GitHub - microsoft/mcp: Catalog of official Microsoft MCP (Model Context Protocol) server implementations for AI-powered data access and tool integration
CLI for m365 MCP server - GitHub - pnp/cli-microsoft365-mcp-server: Manage Microsoft 365 using MCP server
GitHub - dotnet/dev-proxy: Simulate API failures, throttling, and chaos — all from your command line.
By Zoe Wilson and Kevin McDonnell5
22 ratings
Send us a text
Kevin McDonnell and Garry Trinder delve into the world of Model Context Protocol (MCP) and its implications for developers. We start with a starter overview of functionality of MCP and why it is important. However, we wanted to get beyond that initial view that is covered elsewhere and look at some of the challenges associated with using MCP and broader considerations that you need to be looking at. The conversation covers the importance of optimizing documentation for language models, governance in MCP usage, and strategies for getting started with MCP and then scaling.
Takeaways
Useful links
Introduction - Model Context Protocol
Getting started with Local MCP Servers on Claude Desktop | Anthropic Help Center and For Claude Desktop Users – Model Context Protocol (MCP)
Use MCP servers in VS Code
Community built Graph MCP Server - GitHub - merill/lokka: MCP (Model Context Protocol) for Microsoft 365.
Azure AI Search:
Full text search - Azure AI Search | Microsoft Learn
Vector search - Azure AI Search | Microsoft Learn
Hybrid search - Azure AI Search | Microsoft Learn
MCP for beginners course - GitHub - microsoft/mcp-for-beginners
MCP Dev Days 29th/30th July (and available on demand after) - MCP Dev Days | Microsoft Reactor
Microsoft MCP Lab - GitHub - microsoft/mcsmcp: Lab for creating an MCP Server and using it in Microsoft Copilot Studio.
Microsoft's MCP Server collection - GitHub - microsoft/mcp: Catalog of official Microsoft MCP (Model Context Protocol) server implementations for AI-powered data access and tool integration
CLI for m365 MCP server - GitHub - pnp/cli-microsoft365-mcp-server: Manage Microsoft 365 using MCP server
GitHub - dotnet/dev-proxy: Simulate API failures, throttling, and chaos — all from your command line.

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