Give your Agno agents real email access—with oversight modes that let you control exactly how much autonomy each agent gets over outbound messages.
Agno is a Python framework for building production-ready AI agents with tools, memory, knowledge bases, and multi-agent teams. Its emphasis on practical usability over experimental abstractions makes it a natural fit for agents that need to interact with external systems like email.
MultiMail provides a REST API and webhook infrastructure designed specifically for AI agents. Where most email APIs assume a human is composing and sending messages, MultiMail is built around the reality that an agent may be doing the composing—and a human may want to approve the result before it leaves your system.
When you combine Agno teams with MultiMail, you get a clean boundary: agents handle research, drafting, and routing decisions, while MultiMail enforces which messages actually get delivered. A support agent, a research agent, and an operations agent can all share access to a mailbox without any of them being able to send without your approval unless you explicitly grant it.
Agno teams can spawn multiple agents that all want to send email. MultiMail's oversight modes—gated_send, gated_all, monitored, autonomous—apply at the mailbox level, so you configure the trust boundary once rather than patching it into every agent's tool logic.
Set oversight_mode to gated_send and every outbound message from your Agno agents lands in a review queue before delivery. Use the list_pending and decide_email endpoints to approve or reject from a dashboard, webhook, or another agent acting as a reviewer.
MultiMail delivers inbound email to a webhook endpoint you control. Your Agno agent can receive the payload, decide whether to reply or tag or escalate, and call the appropriate API endpoint—all within the same tool-calling loop it already uses.
The get_thread endpoint returns the full message history for a thread. Agno agents can load this as context before replying, which keeps replies coherent across multi-turn email conversations without you manually stitching messages together.
MultiMail checks DKIM, SPF, and DMARC on every inbound message and exposes the results in the read_email payload. Your agents can use this signal to decide whether to trust a message's claimed sender before acting on instructions embedded in it.
No code, no dashboard. Paste this to your AI agent — it connects MultiMail, creates an inbox, and builds the flow for you.
Install Agno with pip and create a MultiMail account to get a live API key. Use a test key (mm_test_...) during development—test keys behave identically to live keys but messages are not delivered externally.
Create a mailbox via the MultiMail dashboard or API. For a new agent integration, start with oversight_mode=gated_send so every outbound message requires your approval before delivery. You can relax this to monitored or autonomous once you trust the agent's behavior.
Write thin wrapper functions around the MultiMail endpoints you need—send_email, check_inbox, reply_email—and pass them to your Agno agent's tools list. Agno will call them automatically when the model decides email action is needed.
Run the agent against a real task. Any outbound messages will land in the approval queue because oversight_mode is gated_send. Call list_pending to see what's queued, then use decide_email to approve or reject each message.
Email infrastructure built for AI agents. Verifiable identity, graduated oversight, and a hosted MCP server. Formally verified in Lean 4.