mailsai

Email API for AI agents — Python SDK.

Per-agent email addresses on your domain, per-agent reputation, and prompt-injection scanning on every inbound. Your agent reads the reply and decides what to say — intent + entity extraction is opt-in.

pip install mailsai

Quick start

No agent to create, no domain to verify, no DNS. from names the sender and the agent is created on first use.

from mailsai import Client

# Reads MAILS_API_KEY from env (or pass api_key=... explicitly)
client = Client()

# mails.ai is transactional-only: mail the recipient asked for. Cold outreach and bulk
# marketing are refused with 422 cold_email_prohibited — that is deliberate, and it is
# what keeps the sending reputation clean for everyone on the platform.
sent = client.send(**{
    "from": "sarah",
    "to": "you@example.com",
    "subject": "Your verification code is 481902",
    "body": "Your verification code is 481902. It expires in 15 minutes.",
})

print(sent["from"])   # sarah@<your-workspace>.mails.ai — which identity actually sent

A test key (mk_test_…) runs that entire path — validation, the firewall, threading, events, webhooks — and delivers nothing, so you can integrate before you decide anything. On a test key, check sent.get("classifier_warning"): it is how a sandbox send tells you the same message would be refused on a live key.

Already have an agent, or want to name it explicitly? Both of these still work:

client.create_agent("sarah")            # explicit creation, when you want it
client.send("sarah", to="…", subject="…", body="…")

Note the free plan allows one agent. If from names a second one and there is no room, the send is refused with 402 plan_limit_exceeded naming the agent you do have — it is never quietly sent under a different identity.

from mailsai import agent

sarah = agent("sarah")

@sarah.on_reply
def handle(reply):
    # Always present — the delivery + security + identity layer:
    # reply["injection_score"]   -> 0.02   # six-category prompt-injection scan
    # reply["sender_reputation"] -> 0.91   # per-agent reputation
    #
    # Present only when classification is enabled (opt-in, +$0.003/inbound):
    # reply["intent"]            -> "schedule_demo" | "ask_question" | …
    # reply["entities"]          -> {"date": "...", "time": "..."}
    # reply["urgency"]           -> 0.8
    #
    # Your agent reads the reply and decides what to send next.
    print(reply["injection_score"], reply["sender_reputation"])

sarah.start_listening()  # blocks; opens SSE stream and dispatches replies

For non-blocking, pass blocking=False to start_listening() — it returns a daemon thread.

Lower-level client

from mailsai import create_client

c = create_client()  # reads MAILS_API_KEY

# Send via any agent
c.send("sarah", to="lead@example.com", subject="Demo", body_text="…")

# Resources
threads = c.list_threads(agent_id="agent_abc123")
usage = c.usage()
rep = c.get_reputation(agent_id="agent_abc123")

# Drafts
draft = c.create_draft(agent="sarah", to="lead@example.com", subject="Demo", body_text="…")
c.send_draft(draft["id"])

Webhook verification

from mailsai import verify_webhook

# In your webhook handler:
event = verify_webhook(
    body=request.body.decode(),
    signature=request.headers["X-Mails-Signature"],
    secret=os.environ["MAILS_WEBHOOK_SECRET"],
)
if event is None:
    return Response(status=400)
# event is the verified inbound event dict

Errors

from mailsai import MailsError

try:
    sarah.send(to="blocked@example.com", subject="…", body="…")
except MailsError as e:
    print(e.type, e.code, e.message, e.status, e.request_id)

Configuration

Documentation

• Full docs: mails.ai/docs
• Source: github.com/RolloutsAI/mailsai

License

MIT