Combine Letta's persistent memory with MultiMail's email infrastructure — agents that remember past email conversations and build relationships over time.
Letta (formerly MemGPT) provides agents with persistent memory that survives across conversations. When combined with MultiMail, your agents can remember past email interactions, track relationship history, and compose contextually aware messages — even weeks after the original conversation.
MultiMail's thread tracking pairs naturally with Letta's archival memory. An agent can store email thread summaries in its long-term memory, retrieve them when a contact emails again, and draft replies that reference prior exchanges. The default gated_send mode ensures a human reviews these context-rich responses before delivery.
Integration uses Letta's tool system. Register MultiMail API functions as tools available to your Letta agent, and the agent can invoke them alongside its memory operations.
Letta agents store email context in archival memory. When a contact emails again, the agent retrieves past interaction summaries to compose informed, relationship-aware replies.
MultiMail tracks email threads, and Letta maintains memory across sessions. Together, your agent can resume an email conversation days later with full context of what was discussed and decided.
As a Letta agent builds memory about reliable email patterns, you can progressively relax oversight from gated_send to monitored. The agent's persistent memory helps it learn appropriate communication styles.
Letta's memory system combined with MultiMail's contact management creates a relationship layer. The agent remembers preferences, past issues, and communication patterns for each contact.
No code, no dashboard. Paste this to your AI agent — it connects MultiMail, creates an inbox, and builds the flow for you.
Sign up at multimail.dev, create a mailbox, and generate an API key from your dashboard. Your key will start with mm_live_.
Install the Letta package and start the Letta server.
Define email functions as Python code strings and register them with the Letta client using create_tool. Create tools for send_email, check_inbox, and reply (wrapping POST /v1/mailboxes/{mailbox_id}/reply/{email_id}).
Create a Letta agent with the email tools attached and a system prompt that explains the oversight mode and instructs the agent to use archival memory for email context.
Review emails queued by the agent in the MultiMail dashboard. Approve messages before delivery. The agent's memory-enhanced context should produce higher-quality drafts over time.
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