mcp-dotnet-samples and MCP-Plugin-dotnet

The "microsoft/mcp-dotnet-samples" project provides comprehensive examples for building MCP servers and clients with .NET, while "IvanMurzak/MCP-Plugin-dotnet" is an ecosystem sibling that offers a specific plugin and lightweight server to expose .NET application methods and data as MCP tools, potentially leveraging the foundational understanding and patterns demonstrated by the samples.

mcp-dotnet-samples
57
Established
MCP-Plugin-dotnet
40
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 15/25
Community 22/25
Maintenance 10/25
Adoption 4/25
Maturity 13/25
Community 13/25
Stars: 157
Forks: 51
Downloads:
Commits (30d): 0
Language: C#
License: MIT
Stars: 8
Forks: 2
Downloads:
Commits (30d): 0
Language: C#
License: Apache-2.0
No Package No Dependents
No Package No Dependents

About mcp-dotnet-samples

microsoft/mcp-dotnet-samples

A comprehensive set of samples of creating and using MCP servers and clients with .NET

This project offers examples for .NET developers to create applications that connect Large Language Models (LLMs) with various data sources and tools. It allows you to feed information from sources like GitHub or Outlook into an LLM and receive outputs that integrate with those systems, such as sending emails or managing to-do lists. This is for software developers building AI-powered applications or agents.

AI application development .NET development LLM integration API integration AI agent building

About MCP-Plugin-dotnet

IvanMurzak/MCP-Plugin-dotnet

.NET MCP bridge: expose app methods/data as MCP tools, prompts, and resources via an in-app plugin + lightweight server (SignalR; stdio/http).

This tool helps .NET developers integrate their desktop applications, game servers, or Unity projects with AI assistants like Claude. It allows the AI to trigger methods, access data, and utilize prompts from a running .NET application. The developer defines what their app can offer, and the AI can then interact with the live application instance.

.NET development AI integration Application interoperability Game development Desktop application development

Scores updated daily from GitHub, PyPI, and npm data. How scores work