agentmail▌
agentmail-to/agentmail-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
API-first email platform giving AI agents dedicated inboxes with send, receive, and management capabilities.
- ›Supports inbox creation with auto-generated or custom email addresses, message sending/receiving, threaded conversations, and label-based organization
- ›Includes attachment handling via Base64 encoding, draft creation for human approval workflows, and message reply functionality
- ›Offers multi-tenant isolation through pods for SaaS platforms, with idempotent operations using clien
AgentMail SDK
AgentMail is an API-first email platform for AI agents. Install the SDK and initialize the client.
Installation
# TypeScript/Node
npm install agentmail
# Python
pip install agentmail
Setup
import { AgentMailClient } from "agentmail";
const client = new AgentMailClient({ apiKey: "YOUR_API_KEY" });
from agentmail import AgentMail
client = AgentMail(api_key="YOUR_API_KEY")
Inboxes
Create scalable inboxes on-demand. Each inbox has a unique email address.
// Create inbox (auto-generated address)
const autoInbox = await client.inboxes.create();
// Create with custom username and domain
const customInbox = await client.inboxes.create({
username: "support",
domain: "yourdomain.com",
});
// List, get, delete
const inboxes = await client.inboxes.list();
const fetchedInbox = await client.inboxes.get({
inboxId: "[email protected]",
});
await client.inboxes.delete({ inboxId: "[email protected]" });
# Create inbox (auto-generated address)
inbox = client.inboxes.create()
# Create with custom username and domain
inbox = client.inboxes.create(username="support", domain="yourdomain.com")
# List, get, delete
inboxes = client.inboxes.list()
inbox = client.inboxes.get(inbox_id="[email protected]")
client.inboxes.delete(inbox_id="[email protected]")
Messages
Always send both text and html for best deliverability.
// Send message
await client.inboxes.messages.send({
inboxId: "[email protected]",
to: "[email protected]",
subject: "Hello",
text: "Plain text version",
html: "<p>HTML version</p>",
labels: ["outreach"],
});
// Reply to message
await client.inboxes.messages.reply({
inboxId: "[email protected]",
messageId: "msg_123",
text: "Thanks for your email!",
});
// List and get messages
const messages = await client.inboxes.messages.list({
inboxId: "[email protected]",
});
const message = await client.inboxes.messages.get({
inboxId: "[email protected]",
messageId: "msg_123",
});
// Update labels
await client.inboxes.messages.update({
inboxId: "[email protected]",
messageId: "msg_123",
addLabels: ["replied"],
removeLabels: ["unreplied"],
});
# Send message
client.inboxes.messages.send(
inbox_id="[email protected]",
to="[email protected]",
subject="Hello",
text="Plain text version",
html="<p>HTML version</p>",
labels=["outreach"]
)
# Reply to message
client.inboxes.messages.reply(
inbox_id="[email protected]",
message_id="msg_123",
text="Thanks for your email!"
)
# List and get messages
messages = client.inboxes.messages.list(inbox_id="[email protected]")
message = client.inboxes.messages.get(inbox_id="[email protected]", message_id="msg_123")
# Update labels
client.inboxes.messages.update(
inbox_id="[email protected]",
message_id="msg_123",
add_labels=["replied"],
remove_labels=["unreplied"]
)
Threads
Threads group related messages in a conversation.
// List threads (with optional label filter)
const threads = await client.inboxes.threads.list({
inboxId: "[email protected]",
labels: ["unreplied"],
});
// Get thread details
const thread = await client.inboxes.threads.get({
inboxId: "[email protected]",
threadId: "thd_123",
});
// Org-wide thread listing
const allThreads = await client.threads.list();
# List threads (with optional label filter)
threads = client.inboxes.threads.list(inbox_id="[email protected]", labels=["unreplied"])
# Get thread details
thread = client.inboxes.threads.get(inbox_id="[email protected]", thread_id="thd_123")
# Org-wide thread listing
all_threads = client.threads.list()
Attachments
Send attachments with Base64 encoding. Retrieve from messages or threads.
// Send with attachment
const content = Buffer.from(fileBytes).toString("base64"How to use agentmail on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add agentmail
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches agentmail from GitHub repository agentmail-to/agentmail-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate agentmail. Access the skill through slash commands (e.g., /agentmail) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★31 reviews- ★★★★★Dhruvi Jain· Dec 20, 2024
agentmail has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Mei Abbas· Dec 16, 2024
Keeps context tight: agentmail is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Camila Mensah· Dec 12, 2024
I recommend agentmail for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Maya Rahman· Dec 8, 2024
agentmail is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Oshnikdeep· Nov 11, 2024
Keeps context tight: agentmail is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Aarav Ndlovu· Nov 7, 2024
agentmail has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aarav Gupta· Nov 3, 2024
Useful defaults in agentmail — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mei Martin· Oct 26, 2024
agentmail fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Meera Bhatia· Oct 22, 2024
Registry listing for agentmail matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ganesh Mohane· Oct 2, 2024
We added agentmail from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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