Email Infrastructure for AI Agents: DNS, Deliverability, and Reputation You Don’t Build

What email infrastructure for AI agents replaces

When a developer ships an agent that sends and receives email, the infrastructure list grows fast: configure an MTA, publish SPF and DKIM records, set up DMARC, warm an IP, monitor bounces and complaints, parse raw MIME, reconstruct threads, and screen inbound for prompt injection. Each of those is a production system. Mails.ai is all of them, already running:

import { createClient } from "@mailsai/sdk";
const mails = createClient({ apiKey: process.env.MAILS_API_KEY });

// Infrastructure handled: SPF/DKIM/DMARC, warm IP, bounce handling.
await mails.messages.send({
  from: "support",              // your agent's authenticated address
  to: "customer@example.com",
  subject: "Your refund #812 is confirmed",
  body_text: "We processed your refund. Reply with any questions.",
});
// The message leaves from an already-warm, DMARC-aligned address.
// Bounce and complaint handling runs automatically.

// Inbound infrastructure: MIME parsing, thread reconstruction,
// prompt-injection scanning — the reply arrives as structured data.
const events = await mails.events.list({
  event_type: "message.received",
  limit: 10,
});
for (const e of events.data) {
  // e.data.extracted_text — clean body, quoted history stripped
  // e.thread_id — stable thread identifier
  // e.injection_score — 0.0–1.0; hold for a person at 0.5+
}

DNS authentication, provisioned per agent

Every agent sends from an address that passes SPF, DKIM, and DMARC alignment. On the shared domain, this is instant — the records exist and the agent inherits them. On a custom domain, you add the generated CNAME and TXT records and verification is automatic. Either way, your agent never touches a DNS console at runtime.

IP reputation and warm-up

New IPs land in spam. Mails.ai solves this two ways: on Free and Pro, agents send from a shared pool of already-warm IPs with an established reputation. On Scale, a dedicated IP warms automatically with your real transactional mail — no manual schedule, no dummy messages. Volume ramps based on actual send patterns.

Reputation is scored per agent: bounce rate, complaint rate, and send volume are tracked independently. If one agent crosses the 0.3 % complaint threshold, it auto-suspends. The rest of your agents keep sending. For the full reputation model, see AI email agent.

Inbound parsing pipeline

The receiving half of the infrastructure turns raw MIME into structured JSON events before your agent sees them. Each inbound message is parsed into sender, subject, extracted text (quoted history stripped), thread ID, and attachments. Every message within the plan’s limits is scanned for prompt injection across six categories; the numeric injection_score arrives on the event so your code branches on a number:

from mailsai import Client

client = Client()  # reads MAILS_API_KEY

events = client.list_events(event_type="message.received", limit=10)
for e in events["data"]:
    score = e.get("injection_score")
    # Hold for a person: quarantined, not scanned, or 0.5+
    if e.get("quarantined") or score is None or score >= 0.5:
        flag_for_review(e)
        continue
    # Safe — route to the agent's reply logic
    handle_reply(e["data"]["extracted_text"], e["thread_id"])

For the full inbound architecture, see the inbound email API for AI agents page. For the parsing layer specifically, see email parsing API.

Cold-email firewall

Shared email infrastructure only stays deliverable if every sender on it sends mail the recipient expects. The cold-email firewall is infrastructure-level, not agent-level: every outbound message is classified before it leaves, and unsolicited outreach returns a 422 cold_email_prohibited without transmitting. This is not configurable, because the alternative is a prompt-injected agent burning the reputation of every other agent on the same sending pool.

Framework and integration support

The infrastructure is accessed through the email API for AI agents — TypeScript SDK, Python SDK, REST API, and MCP server for agent IDEs. Framework guides cover the OpenAI Agents SDK, Anthropic SDK, Vercel AI SDK, and LangGraph. For email management and routing across multiple agents, see AI email management. For the broader overview, see email for AI agents.

Pricing

Every plan includes the full infrastructure: DNS authentication, deliverability, bounce handling, MIME parsing, injection scanning, and per-agent reputation. Free covers one agent with 3,000 emails and 3,000 inbound replies a month — no card required. Pro is $20/month for five agents. Scale is $99/month for unlimited agents and a dedicated IP on request. Yearly billing saves two months. See pricing for the full breakdown.