A Model Context Protocol (MCP) server exposing Gmail operations for AI agents
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# 📧 Agentic Mail MCP > A [Model Context Protocol](https://modelcontextprotocol.io) server that lets AI > agents work with a Gmail account **safely** — read, search, summarize, and > (opt-in) forward/archive/label — behind a layered safety model. > **🔐 You bring your own Google app.** This is a **local tool, not a hosted > service** — you create your own OAuth client in your own Google Cloud project > and authorize your own mailbox. Your credentials and token never leave your > machine, and because the app only ever authorizes you, **there's no central > service and no Google verification to wait for.** > **ℹ️ Status:** `0.1.0` — available on [PyPI](https://pypi.org/project/agentic-mail-mcp/): > `pip install agentic-mail-mcp` (or `uvx agentic-mail-mcp`). ## ✨ Features | | | |---|---| | 📥 **Email operations** | Search, read, forward, archive, delete, draft, and label | | 🧠 **Intelligence** | Caller-first prompts (summarize, classify, reply, action items) + optional server-side digests | | 🔎 **Semantic search** | Natural-language vector search over your mail | | 🔔 **Notifications** | Webhook / Redis event fan-out | | 🛡️ **Railguards** | Read-only by default, allowlists, rate limits, archive-first delete, draft-first send, audit log | ## 🚀 Quick start You need **Python 3.11+** and a Google account. Five minutes end to end. ```mermaid flowchart LR A[1. Install] --> B[2. Google<br/>credentials] B --> C[3. Configure<br/>.env] C --> D[4. Authorize<br/>agentic-mail-mcp auth] D --> E[5. Connect agent<br/>or run HTTP] ``` **1. Install** from PyPI (see [Installation](#-installation) for extras & Docker): ```bash pip install agentic-mail-mcp # or: uvx agentic-mail-mcp ``` **2. Get Google credentials** — in *your* Google Cloud project, enable the Gmail API, make a **Desktop-app OAuth client**, and **download its `credentials.json`**. Full walkthrough with the exact clicks: [Getting your Google credentials 👉](specs/docs/configuration.md#…
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