How agents should think about email.
Architecture, patterns, and deliverability from the team building email infrastructure for AI agents.
We write about agent email patterns, deliverability, and security. These posts explain the decisions behind the API. They’re technical. We don’t write fluff. Pick the topic that matters to you right now.
AI Email API: Give Your AI Agent Its Own Email Address
Learn how to provision a dedicated email address for your AI agent using DNS, SMTP, and inbound webhooks. Covers addressing, authentication, and thread management.
Giving Your AI Agent an Inbox: Routing, Parsing & Webhooks
Learn how to give your AI agent a real inbox: DNS routing, MIME parsing, webhook delivery, and idempotency patterns for production systems.
Email Automation AI: Building Autonomous Agent Email Pipelines
A technical guide to email automation AI for developers: how autonomous AI agents send, receive, classify, and act on email using purpose-built API infrastructure.
Sending Transactional Email from AI Agents: OTPs, Links, Notifications
Learn how AI agents should send OTPs, magic links, and notifications with correct headers, idempotency keys, rate limits, and deliverability controls.
Mails.ai vs AgentMail: Email API for AI Agents
Mails.ai vs AgentMail compared on architecture, pricing, MCP support, inbound parsing, and deliverability for AI agent email workflows.
Parsing Email Attachments for LLM Ingestion
A technical guide to extracting, normalizing, and feeding email attachments into LLMs — covering MIME parsing, PDF extraction, OCR, and chunking strategies.
Transactional vs AI Agent Email: Architectural Differences
Deep dive into the core architectural differences between transactional email and AI agent email — threading, state, inbound parsing, and deliverability.
Inbound Email Processing for AI Agents: Classification, Routing, Actions
How AI agents classify, route, and act on inbound email: parsing raw MIME, intent classification, routing logic, and triggering deterministic actions reliably.
RFC-Compliant Email Replies from AI Agents
Learn how AI agents can compose RFC 5322-compliant email replies with correct threading headers, MIME structure, and quoting conventions.
Designing Idempotent Email Sending for AI Agents
Learn how to design idempotent email sending systems for AI agents — covering idempotency keys, deduplication stores, retry logic, and delivery guarantees.
How AI Agents Should Handle Email Replies
A technical guide to threading, reply detection, context management, and response generation for AI agents that send and receive email.
Building an Email-Driven Agent Workflow
Learn how to build production-grade email-driven agent workflows: inbound parsing, state machines, threading, tool dispatch, and deliverability for automated senders.
Structured Reply Events for Email Agents
Learn how to design structured reply events so your email agents can parse, route, and act on inbound replies with precision — covering schemas, threading, and idempotency.
Email API for AI Agents: Architecture & Provider Guide
Compare email API providers for AI agents. Covers MCP support, inbound parsing, deliverability, and architecture — with a clear recommendation for agent builders.
How to Build an MCP Email Server for AI Agents
Learn how to build an MCP email server that lets AI agents send, receive, and parse email via the Model Context Protocol — with real code and architecture.
Webhook-Based Inbound Email Processing for AI Agents
Learn how to build reliable webhook-based inbound email pipelines for AI agents — parsing, routing, threading, and handling edge cases at scale.
Transactional vs Agent Email Architecture
Learn the core architectural differences between transactional and agent email systems—covering SMTP flows, inbound parsing, threading, webhooks, and MCP integration.
Structured reply events — why your agent should never read raw email
Most email APIs hand your agent a string body. Mails.ai parses every inbound into a structured reply event — injection score and sender reputation on every event, opt-in classification for intent, entities, and urgency — so your code reads against a structured object, not raw bytes.
Prompt injection in inbound email is a real RCE class. Here's how mails.ai scans for it.
Prompt injection in agent runtimes is a tracked vulnerability class — Microsoft Security Response Center publishes AI-security advisories, OWASP catalogues it as LLM01. The vulnerability is structural: any agent that reads raw inbound text is exposed. Mails.ai runs a six-category scanner on every inbound before the structured reply event reaches your code, and flags high-confidence attacks (`quarantined`) so your agent skips them.
Per-event metered pricing: why monthly tiers force over-commit
Resend wants $20/month whether your agent sends 0 or 50,000 emails. Postmark wants $50. Agent traffic is bursty by nature — quiet days and incident spikes — so monthly tiers structurally force over-commit. Per-event metered pricing aligns cost to what you actually use, and incumbents cannot match without rebuilding their economics.
MCP-native email — `from mails import agent` becomes the default agent comms primitive
MCP collapsed N runtimes × M SDKs into one server that every runtime can use. Mails.ai shipped MCP-native from day one — drop a JSON snippet into your runtime config and your agent gets send, on_reply, list_threads, and get_reputation tools automatically.
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Public API opens Q3 2026. Drop ~6 lines into your agent and ship.
$ npm install @mailsai/sdk