m365-radar
An MCP server that provides offline searchable Microsoft 365 roadmap data and live Azure status, enabling AI agents to answer questions about upcoming features, roadmap changes, and Azure incidents.
README
m365-radar
An MCP server and an open daily dataset for the Microsoft 365 roadmap and Azure service status.
Point an AI agent at it and ask what is coming for Intune next quarter, what changed on the roadmap this week, or whether Azure is currently degraded — without anyone opening a browser.
Why a snapshot instead of a live proxy
The roadmap API is undocumented, bot-protected and about 2 MB per request. Querying it on every tool call would be slow and fragile, so this repo does it the other way round:
- A GitHub Action harvests the roadmap once a day and commits a normalised snapshot to
data/. - The MCP server answers queries from that snapshot — fast, offline-capable, and unaffected if the upstream endpoint has a bad day.
- The git history becomes the changelog. The diff between two daily commits is exactly what Microsoft changed on the roadmap, with nothing else in it.
That last point is the radar. git log -p -- data/roadmap.json is a complete, auditable record of roadmap movement over time.
The harvest commits every day so you can see it ran, but the commit message says which kind of day it was: data: roadmap changed … when Microsoft moved something, chore: roadmap unchanged … when they did not.
Tools
| Tool | What it does |
|---|---|
search_roadmap |
Free-text search with filters for product, status, cloud instance and platform |
get_roadmap_item |
Full detail for one feature ID |
list_recent_changes |
Features added or updated in the last N days — newest first |
get_azure_status |
Active Azure incidents, read live from the public status feed |
Statuses are In development, Rolling out, Launched and Cancelled. Cloud instances are Worldwide (Standard Multi-Tenant), GCC, GCC High and DoD.
Use it with Claude Code
git clone https://github.com/DimaVasilenko-Intune/m365-radar.git
cd m365-radar
npm install
npm run harvest # fetch the first snapshot
npm run build
claude mcp add m365-radar -- node "$(pwd)/dist/server.js"
Any other MCP client works the same way — it is a plain stdio server:
{
"mcpServers": {
"m365-radar": {
"command": "node",
"args": ["/absolute/path/to/m365-radar/dist/server.js"]
}
}
}
The dataset
data/roadmap.json is a normalised array of every published roadmap feature, sorted by ID with a fixed key order so diffs stay clean. data/meta.json records when it was harvested and the full product, platform and cloud-instance taxonomy.
Each feature carries id, title, description, status, products, cloudInstances, platforms, releasePhases, previewDate, generalAvailabilityDate, created, modified, moreInfoLink and a url deep link.
The data is Microsoft's; this repo only reshapes it. Use it for whatever you like.
Your clone does not refresh itself. This repository is updated daily, but a checkout on your machine stays at whatever commit you pulled. Every tool response reports snapshotAgeDays, and once your copy is three days old it also returns a warning telling you to git pull or run npm run harvest. Keeping it current is a pull, or a git pull on a schedule if you would rather not think about it.
Data sources
| Source | Endpoint |
|---|---|
| Microsoft 365 roadmap | https://www.microsoft.com/releasecommunications/api/v1/m365 |
| Azure status | https://azure.status.microsoft/en-us/status/feed/ |
Be aware: the roadmap endpoint is not a documented, supported API. It returns 403 unless the request carries a browser User-Agent, and Microsoft can change or withdraw it without notice. The snapshot design means a bad upstream day costs you freshness, not availability — the harvest refuses to overwrite a good snapshot with an empty or malformed response.
No tenant data, no authentication and no Microsoft Graph calls are involved anywhere in this project. Everything here is public information.
Development
npm run harvest # refresh data/ from upstream
npm run dev # run the server from source
npm run build # compile to dist/
License
MIT © Dima Vasilenko
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。