MailMind: An AI Agent That Actually Handles Email Scheduling Why I built this Scheduling meetings over email is surprisingly painful. You send one mail, then it turns into a long thread: “Are you free Tuesday?” “No, what about Wednesday?” “Let’s do next week.” …and it just keeps going. The problem isn’t email itself — it’s that we’re using an unstructured system to solve a structured task. Most tools try to fix this, but they all require behavior change: Calendly → click a link AI assistants → draft replies, but don’t act Bots → break in real conversations I wanted to try something different: what if the system just worked inside email, without changing how people use it? MailMind is an AI agent that joins an email thread and handles scheduling end-to-end. You just CC it once. From there, it: reads the conversation understands availability from natural language follows up if something is unclear finds a common time creates a calendar event sends confirmations No links. No UI. No extra steps. Everything happens inside the same email thread. At a high level, the system is event-driven. An incoming email triggers the entire pipeline: Gmail pushes an event backend fetches full thread data agent processes it system decides what to do next Instead of writing this as a linear script, I used a state-based agent loop. Each step in the flow is a node: classify the email extract availability check if something is missing compute overlaps generate a response The agent moves between these states depending on what it sees in the thread. The LLM is not running the whole system. It’s only used where natural language is involved: understanding emails detecting ambiguity rewriting responses Everything else is deterministic: time parsing overlap calculation slot ranking calendar operations This separation makes the system more reliable. Each email thread is treated as a persistent session: who has replied what time slots they gave who is pending preferences (like “no Fridays”) This state is stored in SQLite and updated after every email. A scoring function ranks slots based on: attendance preferences priority participants time optimization The system selects the most practical option, not just the first valid one. Before sending any email: draft goes to Telegram approve / reject / edit auto-send fallback Tech Stack Python FastAPI LangGraph Gemini 2.0 Flash SQLite React Gmail API Google Calendar API Telegram Bot API Final thought Most AI tools assist. This one acts. It takes something messy (email threads) and turns it into a structured, executable workflow. That’s where AI becomes actually useful.