Wire Cohere tool use, classification, and reranking to MultiMail's REST API to give your agents production-ready email capabilities with approval gates and audit trails.
Cohere's platform covers the full range of enterprise AI tasks — generation, embeddings, reranking, and classification — making it a strong foundation for agents that need more than a single model's capabilities. Many teams reach for Cohere specifically when they want provider flexibility, on-premises deployment, or retrieval pipelines that combine generation with semantic search.
Connecting Cohere to email introduces the same set of production concerns it always does: approval flows, deliverability, rate limits, and audit trails. Cohere's API doesn't enforce any of these — it generates text and returns tool calls. MultiMail handles the email layer, including gated send modes that require human sign-off before any message leaves your infrastructure.
The integration follows Cohere's standard tool-use loop. You define MultiMail endpoints as tools, run the chat loop, and execute the function calls against MultiMail's REST API. Classification and reranking can run before or after inbox retrieval to filter, prioritize, or route messages without the model needing to reason about every email in a large inbox.
Cohere generates a tool call to send_email and stops. MultiMail's gated_send mode holds that message in a pending queue until a human approves it via the list_pending and decide_email endpoints. Your agent code doesn't change — the gate is enforced server-side.
MultiMail exposes check_inbox, send_email, reply_email, read_email, tag_email, and decide_email as stable REST endpoints. You can register these directly as Cohere tools and rely on consistent schemas across model versions.
Cohere's rerank model can prioritize emails returned by check_inbox before passing them to the generation model. This reduces context length and prevents the LLM from burying high-priority messages when the inbox is large.
Cohere's classify endpoint can label incoming emails by category, urgency, or sender type using a small example set. Pass those labels to MultiMail's tag_email endpoint to route messages before the generation model ever sees them.
Rate limits, send-time windows, and domain allowlists are enforced by MultiMail regardless of what Cohere's model outputs. An agent that hallucinates a send call to an off-hours recipient gets queued, not delivered.
No code, no dashboard. Paste this to your AI agent — it connects MultiMail, creates an inbox, and builds the flow for you.
Install the Cohere Python client. Create a MultiMail account and provision a mailbox — use a custom domain or a @multimail.dev address for testing.
Register check_inbox, send_email, and any other MultiMail endpoints your agent needs as tools in the Cohere tool format. Keep parameter descriptions specific — Cohere's model uses them to decide when and how to call each tool.
Call co.chat with your tools list, detect tool_calls in the response, dispatch each call to the corresponding MultiMail endpoint, and feed results back into the message history until the model returns a final text response.
Update the mailbox oversight_mode as you build confidence in agent behavior. Start with gated_send so every outbound message is reviewed, then move to monitored once the agent's output quality is established. You can change this via the MultiMail dashboard or the create_mailbox API.
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