msteams-mcp
MCP server for Microsoft Teams that lets AI assistants search, message, and manage chats, meetings, files, and contacts using your existing Teams browser login—no app approval or Azure AD registration needed.
README
Microsoft Teams MCP Server
MCP server for Microsoft Teams — search, message, and manage chats with browser-session auth; no Teams app approval or Azure AD registration.
Clone the repo, build it, point your AI tool at dist/index.js. Talks to the same Teams APIs the web app uses (Substrate, chatsvc, CSA). Auth is your normal Teams browser login; access matches what your account can already do.
Prerequisites
- Node.js 18+
- Microsoft account with Teams access
- Chrome (macOS/Linux) or Edge (Windows)
Setup
git clone https://github.com/hickeroar/msteams-mcp.git
cd msteams-mcp
npm install
npm run build
Register it as a local stdio MCP server in whatever AI tool you use (Cursor, Claude Desktop, Claude Code, Augment, Windsurf, etc.). The shape is always the same: run node with the absolute path to dist/index.js.
{
"mcpServers": {
"MS Teams": {
"command": "node",
"args": ["/absolute/path/to/msteams-mcp/dist/index.js"]
}
}
}
Where that config lives depends on the client (examples):
| Client | Typical config location |
|---|---|
| Cursor | ~/.cursor/mcp.json (or project .cursor/mcp.json) |
| Claude Desktop | Claude → Settings → Developer → Edit Config (claude_desktop_config.json) |
| Claude Code | MCP settings / .mcp.json as documented for your version |
| Augment | Augment MCP / tools settings (add a local stdio server) |
Exact UI labels vary; look for “MCP servers”, “Model Context Protocol”, or “custom tools”, then add a command + args (stdio) entry like above. Use an absolute path.
Restart or reload MCP/tools in that client after changing config or rebuilding.
First login
Ask the assistant (in Cursor, Claude, Augment, etc.) to call teams_login (soft {} first; use forceNew: true if the session is dead). A browser opens for Microsoft/SSO sign-in. Session files are saved under:
- macOS/Linux:
~/.teams-mcp-server/ - Windows:
%APPDATA%\teams-mcp-server\
After that, tools use cached tokens. Tokens refresh automatically when possible; call teams_login again if auth fails.
After pulling code changes
npm install
npm run build
Then restart/reload the Teams MCP server in your AI client so it loads the new dist/.
Useful commands
npm run build # compile to dist/
npm run typecheck # tsc --noEmit
npm start # run compiled MCP server (stdio)
npm run cli # CLI with the same tools (no build required)
npm run cli -- status
npm run cli -- login
npm run cli -- find_channel --query "general"
The CLI shares the same session as the MCP server and is handy for debugging outside any AI client.
Available tools
Search & discovery
| Tool | Description |
|---|---|
teams_search |
Search Teams messages with operators (from:, sent:, in:, etc.) |
teams_search_email |
Search emails in your mailbox |
teams_list_chats |
List recent conversations with last-message preview |
teams_get_message |
Get a single message by ID (includes reactions) |
teams_get_thread |
Get messages from a conversation/thread; since, threadRootId, fromUrl |
teams_find_channel |
Find channels by name (membership list; works without Substrate) |
teams_get_activity |
Activity feed (mentions, reactions, replies, notifications) |
Messaging
| Tool | Description |
|---|---|
teams_send_message |
Send a message (markdown); thread reply, subject, schedule, content type |
teams_wait_for_reply |
Block until a new message arrives (capped ~110s) |
teams_edit_message |
Edit one of your own messages |
teams_delete_message |
Soft-delete one of your own messages |
People & contacts
| Tool | Description |
|---|---|
teams_get_me |
Current user profile |
teams_search_people |
Search people by name or email |
teams_get_frequent_contacts |
Frequently contacted people |
teams_get_person |
Resolve MRI(s) to full profiles |
teams_get_chat |
Conversation ID for a 1:1 chat |
teams_create_group_chat |
Create a group chat (2+ others) |
Organisation
| Tool | Description |
|---|---|
teams_get_favorites |
Pinned/favourite conversations |
teams_add_favorite |
Pin a conversation |
teams_remove_favorite |
Unpin a conversation |
teams_save_message |
Bookmark a message |
teams_unsave_message |
Remove bookmark |
teams_get_saved_messages |
List saved messages |
teams_get_followed_threads |
List followed threads |
teams_get_unread |
Unread counts (aggregate or per conversation) |
teams_mark_read |
Mark a conversation read up to a message |
teams_get_tags |
Channel tags for a team (teamId from teams_find_channel) |
Reactions
| Tool | Description |
|---|---|
teams_search_emoji |
Search standard + custom org emojis |
teams_add_reaction |
Add a reaction to a message |
teams_remove_reaction |
Remove a reaction |
Quick reactions without search: like, heart, laugh, surprised, sad, angry.
Calendar & meetings
| Tool | Description |
|---|---|
teams_get_meetings |
Calendar meetings (default: next 7 days) |
teams_get_transcript |
Meeting transcript (threadId from teams_get_meetings) |
Files
| Tool | Description |
|---|---|
teams_get_shared_files |
Files and links shared in a conversation |
Session
| Tool | Description |
|---|---|
teams_login |
Manual login (opens browser) |
teams_status |
Auth / session status |
Channel reads usually work via teams_find_channel → teams_get_thread even when Substrate search (teams_search) is unavailable. Architecture notes: AGENTS.md. API details: docs/API-REFERENCE.md.
Limitations
- Browser login required once (and again if the session fully expires)
- Undocumented Microsoft APIs; they can change
- Search is full-text only; use
teams_get_threadfor full thread context - Edit/delete only your own messages
License
MIT
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。