Awesome Copilot MCP Server
平台与服务by microsoft
可保存 Awesome Copilot 仓库中 Copilot 自定义配置的 MCP server,便于集中管理与复用个性化设置。
把 Awesome Copilot 的个性化配置集中托管到 MCP Server,解决设置分散、迁移复用麻烦的问题,团队协作会省心很多。
什么是 Awesome Copilot MCP Server?
可保存 Awesome Copilot 仓库中 Copilot 自定义配置的 MCP server,便于集中管理与复用个性化设置。
README
Model Context Protocol .NET Samples
🚀 Introduction
Welcome to the Model Context Protocol (MCP) .NET Samples repository! This collection of samples demonstrates how to leverage the Model Context Protocol in .NET applications.
MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). Think of MCP like a USB-C port for AI applications - it provides a standardized way to connect AI models to different data sources and tools.
With MCP, you can:
- Utilize pre-built integrations that your LLM can directly plug into
- Flexibly switch between LLM providers and vendors
- Follow best practices for securing your data within your infrastructure
- Build agents and complex workflows on top of LLMs
This repository contains .NET samples ranging from building your own MCP implementation to integrating with Azure services.
📋 Sample Projects
| Sample Name | Install | Description |
|---|---|---|
| Awesome Copilot | MCP server that retrieves GitHub Copilot customization files from awesome-copilot. | |
| Markdown to HTML | MCP server that converts markdown text to HTML. | |
| Outlook Email | MCP server that sends emails through Outlook. | |
| To-do List | MCP server that manages to-do list items. |
🛠️ Getting Started
Details on how to set up and run the samples will be provided in each sample's directory.
📚 Learning Resources
🚶♀️ Next Steps
- Learn more about GenAI with .NET with a free course!
- Join the Azure AI Community Discord to keep the conversation going
Contributing
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
Trademarks
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.
常见问题
Awesome Copilot MCP Server 是什么?
可保存 Awesome Copilot 仓库中 Copilot 自定义配置的 MCP server,便于集中管理与复用个性化设置。
相关 Skills
Slack动图
by anthropics
面向Slack的动图制作Skill,内置emoji/消息GIF的尺寸、帧率和色彩约束、校验与优化流程,适合把创意或上传图片快速做成可直接发送的Slack动画。
✎ 帮你快速做出适配 Slack 的动图,内置约束规则和校验工具,少踩上传与播放坑,做表情包和演示都更省心。
MCP构建
by anthropics
聚焦高质量 MCP Server 开发,覆盖协议研究、工具设计、错误处理与传输选型,适合用 FastMCP 或 MCP SDK 对接外部 API、封装服务能力。
✎ 想让 LLM 稳定调用外部 API,就用 MCP构建:从 Python 到 Node 都有成熟指引,帮你更快做出高质量 MCP 服务器。
接口测试套件
by alirezarezvani
扫描 Next.js、Express、FastAPI、Django REST 的 API 路由,自动生成覆盖鉴权、参数校验、错误码、分页、上传与限流场景的 Vitest 或 Pytest 测试套件。
✎ 帮你把API与集成测试自动化跑顺,减少回归漏测;能力全面,尤其适合复杂接口场景的QA团队。
相关 MCP Server
Slack 消息
编辑精选by Anthropic
Slack 是让 AI 助手直接读写你的 Slack 频道和消息的 MCP 服务器。
✎ 这个服务器解决了团队协作中需要 AI 实时获取 Slack 信息的痛点,特别适合开发团队让 Claude 帮忙汇总频道讨论或发送通知。不过,它目前只是参考实现,文档有限,不建议在生产环境直接使用——更适合开发者学习 MCP 如何集成第三方服务。
by netdata
io.github.netdata/mcp-server 是让 AI 助手实时监控服务器指标和日志的 MCP 服务器。
✎ 这个工具解决了运维人员需要手动检查系统状态的痛点,最适合 DevOps 团队让 Claude 自动分析性能数据。不过,它依赖 NetData 的现有部署,如果你没用过这个监控平台,得先花时间配置。
by d4vinci
Scrapling MCP Server 是专为现代网页设计的智能爬虫工具,支持绕过 Cloudflare 等反爬机制。
✎ 这个工具解决了爬取动态网页和反爬网站时的头疼问题,特别适合需要批量采集电商价格或新闻数据的开发者。不过,它依赖外部浏览器引擎,资源消耗较大,不适合轻量级任务。