outlook-mcp

outlook-mcp

An MCP server that gives AI agents structured access to a Microsoft Outlook mailbox through the Microsoft Graph API, with a deliberate constraint: agents can read and draft emails, but only humans can send.

Category
Visit Server

README

outlook-mcp

An MCP server that gives AI agents structured access to a Microsoft Outlook mailbox through the Microsoft Graph API — with one deliberate constraint at its core:

Agents read and draft. Only humans send.

There is no send tool in this server, and the OAuth token it holds does not include the Mail.Send scope. Even a fully compromised or badly prompted agent cannot send email through it — the capability doesn't exist at the token level. Everything outbound lands in your Drafts folder for human review.

I built this to power an autonomous operations pipeline: scheduled headless agent sessions sweep the mailbox twice a day, reconcile every open commitment and follow-up into a dashboard, and queue reply drafts for review. It runs identically under Claude Code and OpenAI Codex — one integration layer, two vendors' agents.

Permission model

Capability Agent Notes
List/search/read mail Full mailbox visibility
Organize (folders, move, batch triage) Reversible operations only
Create drafts / reply drafts Lands in Drafts, never sent
Send email No tool, and no Mail.Send scope on the token
Delete email Not implemented

Auth is MSAL Authorization Code Flow with PKCE through a localhost-only callback. Tokens cache to ~/.outlook-mcp/ with 0600 permissions.

Tools (10)

Tool Purpose
list_folders Folder tree with counts
create_folder Create a mail folder
list_emails Page through a folder (subject, sender, preview, unread)
search_emails KQL search across all folders (from:, subject:, free text)
read_email Full message body (HTML converted to clean text), recipients, attachments list
move_emails Move messages between folders
batch_move_emails Bulk triage in one call
create_draft New outbound draft
create_reply_draft Reply/reply-all draft on an existing thread
summarize_folder Folder statistics (volume, unread, top senders)

Setup

1. Register a (free) app in Entra ID

Microsoft Entra admin center → App registrations → New registration:

  • Supported account types: your tenant only, or multi-tenant + personal accounts (then use OUTLOOK_MCP_TENANT_ID=common)
  • Redirect URI: platform Mobile and desktop applications → add http://localhost:3847/auth/callback
  • Authentication → enable Allow public client flows
  • API permissions → Microsoft Graph → DelegatedMail.ReadWrite, MailboxSettings.Read

No client secret is needed (public client + PKCE).

2. Build and authenticate

npm install
npm run build

export OUTLOOK_MCP_CLIENT_ID=<your app client id>
export OUTLOOK_MCP_TENANT_ID=<your tenant id or "common">

npm run auth   # opens browser once; token cache persists at ~/.outlook-mcp/

3. Connect an agent

Claude Code.mcp.json in your project (or claude mcp add):

{
  "mcpServers": {
    "outlook": {
      "command": "node",
      "args": ["/path/to/outlook-mcp/dist/index.js"],
      "env": {
        "OUTLOOK_MCP_CLIENT_ID": "<client id>",
        "OUTLOOK_MCP_TENANT_ID": "<tenant id>"
      }
    }
  }
}

OpenAI Codex~/.codex/config.toml:

[mcp_servers.outlook]
command = "node"
args = ["/path/to/outlook-mcp/dist/index.js"]
env = { OUTLOOK_MCP_CLIENT_ID = "<client id>", OUTLOOK_MCP_TENANT_ID = "<tenant id>" }

Same server, same tools, either agent. That portability is the point of MCP.

Architecture

┌─────────────┐     stdio      ┌──────────────┐     HTTPS     ┌─────────────────┐
│ Claude Code │◄──────────────►│              │◄─────────────►│ Microsoft Graph │
├─────────────┤   JSON-RPC     │  outlook-mcp │   REST v1.0   │  /me/messages   │
│ OpenAI Codex│◄──────────────►│  (Node/TS)   │               │  /me/mailFolders│
└─────────────┘                └──────┬───────┘               └─────────────────┘
                                      │
                               ┌──────┴───────┐
                               │ MSAL + PKCE  │  Mail.ReadWrite only —
                               │ token cache  │  no Mail.Send on the token
                               └──────────────┘
  • Transport: stdio (JSON-RPC), one process per agent session
  • Auth: MSAL Auth Code Flow + PKCE, localhost callback, silent refresh from disk cache
  • Bodies: HTML mail converted to clean plain text before it reaches the model (token efficiency)
  • Validation: every tool input validated with zod before any Graph call

Development

npm run dev       # tsc --watch
npm run inspect   # MCP Inspector against the built server

License

MIT © Don Fournier

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured