agentmail

Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses (e.g. hermes-agent@agentmail.to).

3,891 stars

Best use case

agentmail is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses (e.g. hermes-agent@agentmail.to).

Teams using agentmail should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/agentmail-2/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/agungprabowo123/agentmail-2/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/agentmail-2/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How agentmail Compares

Feature / AgentagentmailStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses (e.g. hermes-agent@agentmail.to).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# AgentMail — Agent-Owned Email Inboxes

## Requirements

- **AgentMail API key** (required) — sign up at https://console.agentmail.to (free tier: 3 inboxes, 3,000 emails/month; paid plans from $20/mo)
- Node.js 18+ (for the MCP server)

## When to Use
Use this skill when you need to:
- Give the agent its own dedicated email address
- Send emails autonomously on behalf of the agent
- Receive and read incoming emails
- Manage email threads and conversations
- Sign up for services or authenticate via email
- Communicate with other agents or humans via email

This is NOT for reading the user's personal email (use himalaya or Gmail for that).
AgentMail gives the agent its own identity and inbox.

## Setup

### 1. Get an API Key
- Go to https://console.agentmail.to
- Create an account and generate an API key (starts with `am_`)

### 2. Configure MCP Server
Add to `~/.hermes/config.yaml` (paste your actual key — MCP env vars are not expanded from .env):
```yaml
mcp_servers:
  agentmail:
    command: "npx"
    args: ["-y", "agentmail-mcp"]
    env:
      AGENTMAIL_API_KEY: "am_your_key_here"
```

### 3. Restart Hermes
```bash
hermes
```
All 11 AgentMail tools are now available automatically.

## Available Tools (via MCP)

| Tool | Description |
|------|-------------|
| `list_inboxes` | List all agent inboxes |
| `get_inbox` | Get details of a specific inbox |
| `create_inbox` | Create a new inbox (gets a real email address) |
| `delete_inbox` | Delete an inbox |
| `list_threads` | List email threads in an inbox |
| `get_thread` | Get a specific email thread |
| `send_message` | Send a new email |
| `reply_to_message` | Reply to an existing email |
| `forward_message` | Forward an email |
| `update_message` | Update message labels/status |
| `get_attachment` | Download an email attachment |

## Procedure

### Create an inbox and send an email
1. Create a dedicated inbox:
   - Use `create_inbox` with a username (e.g. `hermes-agent`)
   - The agent gets address: `hermes-agent@agentmail.to`
2. Send an email:
   - Use `send_message` with `inbox_id`, `to`, `subject`, `text`
3. Check for replies:
   - Use `list_threads` to see incoming conversations
   - Use `get_thread` to read a specific thread

### Check incoming email
1. Use `list_inboxes` to find your inbox ID
2. Use `list_threads` with the inbox ID to see conversations
3. Use `get_thread` to read a thread and its messages

### Reply to an email
1. Get the thread with `get_thread`
2. Use `reply_to_message` with the message ID and your reply text

## Example Workflows

**Sign up for a service:**
```
1. create_inbox (username: "signup-bot")
2. Use the inbox address to register on the service
3. list_threads to check for verification email
4. get_thread to read the verification code
```

**Agent-to-human outreach:**
```
1. create_inbox (username: "hermes-outreach")
2. send_message (to: user@example.com, subject: "Hello", text: "...")
3. list_threads to check for replies
```

## Pitfalls
- Free tier limited to 3 inboxes and 3,000 emails/month
- Emails come from `@agentmail.to` domain on free tier (custom domains on paid plans)
- Node.js (18+) is required for the MCP server (`npx -y agentmail-mcp`)
- The `mcp` Python package must be installed: `pip install mcp`
- Real-time inbound email (webhooks) requires a public server — use `list_threads` polling via cronjob instead for personal use

## Verification
After setup, test with:
```
hermes --toolsets mcp -q "Create an AgentMail inbox called test-agent and tell me its email address"
```
You should see the new inbox address returned.

## References
- AgentMail docs: https://docs.agentmail.to/
- AgentMail console: https://console.agentmail.to
- AgentMail MCP repo: https://github.com/agentmail-to/agentmail-mcp
- Pricing: https://www.agentmail.to/pricing

Related Skills

agentmail-to-inbox-ops

3891
from openclaw/skills

Manage Agentmail.to inbox operations with deterministic Python scripts: list/read messages, download and analyze attachments, reply with sender filters, and set read/unread state. Use when handling inbox workflows for any Agentmail.to inbox.

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891
from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure

linkedin-cli

3891
from openclaw/skills

A bird-like LinkedIn CLI for searching profiles, checking messages, and summarizing your feed using session cookies.

Content & Documentation

notebooklm

3891
from openclaw/skills

Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成(播客、视频、幻灯片、测验、思维导图等)、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。

Data & Research