AI Meeting Scheduler

Part of the worlds-biggest-software-project initiative.

An open-source, AI-native meeting scheduler that learns user preferences and coordinates calendars without the friction of incumbent tools.

The AI Meeting Scheduler is a self-hostable scheduling platform for individuals, distributed teams, and executive assistants who need intelligent calendar coordination across Google Calendar, Outlook, and CalDAV-compatible systems. It combines link-based booking, focus-time protection, and preference-learning AI into a single tool, replacing the patchwork of proprietary SaaS products that dominate the category today.

Why AI Meeting Scheduler?

Calendly is rule-based, not preference-learning. It dominates booking flows but offers no AI personalisation, no autonomous outbound scheduling, and gates webhooks behind paid plans.
Motion and Reclaim.ai are proprietary and feature-dense. Both are powerful but require trust in opaque rescheduling logic, suffer from steep onboarding, and lock users into closed SaaS ($10–$34/month).
Clara and Lindy are inaccessible. The autonomous email-agent category is gated by enterprise pricing or usage-based models that penalise high-volume users.
Cal.com is the only major open-source option but its AI features (Cal.ai) are still maturing relative to Motion and Reclaim, leaving room for an AI-native open-source alternative.
Cross-organisation agent negotiation does not exist. No tool today automates scheduling between two AI agents at different companies without a shared platform.

Key Features

Calendar Sync and Booking

Real-time free/busy detection across Google Calendar, Microsoft Outlook, Apple Calendar, and CalDAV feeds
Shareable scheduling links with customisable availability windows and event types
iCalendar / .ics invite generation and delivery
Timezone detection and multi-timezone display
Round-robin and collective event types for team scheduling

AI Scheduling Intelligence

Preference-learning engine that infers optimal meeting windows from accepted and declined meeting history
AI slot suggestion based on stated preferences (time-of-day, buffer time, meeting type)
Focus-block protection that detects and defends deep-work periods automatically
Dynamic rescheduling when deadlines or priorities shift in connected project tools

Team and Workflow Integration

Routing forms with conditional logic for lead distribution
Task integration with tools such as Linear, Todoist, Asana, ClickUp, and Jira
Webhook API for third-party integrations
Basic team analytics covering meeting load and focus-time ratio
Email reminders, confirmations, and post-meeting follow-up

Autonomous Agent Capabilities (Backlog)

Email-based scheduling agent that handles back-and-forth negotiation via CC, in the style of Lindy and Clara
Multi-agent cross-organisation negotiation via MCP or open protocol
Burnout and workload monitoring with auto-declination suggestions
Context-aware meeting preparation that attaches relevant documents and prior notes to events

AI-Native Advantage

Where incumbents apply rule-based logic (Calendly) or opaque heuristics (Motion, Reclaim), this project centres on transparent preference learning, multi-party negotiation between AI agents, contextual meeting preparation, and burnout-aware scheduling. AI infers ideal windows, buffer times, and energy patterns from historical calendar behaviour without explicit configuration, and surfaces explanations that users can audit and override in natural language.

Tech Stack & Deployment

The project targets self-hosted and cloud deployment modes, with full data ownership for self-hosters. It is built on open standards: CalDAV (RFC 4791) for calendar sync, iCalendar (RFC 5545) for event exchange, OAuth 2.0 for delegated calendar access, and Microsoft Graph API for Outlook/Exchange integration. A REST API with OpenAPI specification, webhook subscriptions, and an embeddable booking widget mirror the integration surface offered by Cal.com and Calendly.

Market Context

The AI calendar and scheduling market was valued at $21.42 billion in 2025 and is projected to reach $27.8 billion in 2026 at a 29.8% CAGR, with forecasts of $78.14 billion by 2030 (Research and Markets, 2026). Pro plans cluster at $10–$20/month, team plans at $15–$35/user/month, and autonomous agents like Clara command enterprise pricing above $100/month. Primary buyers are executives and consultants protecting deep-work time, sales teams running high-volume prospect calls, distributed engineering teams across time zones, and HR/recruiting coordinators managing interview loops.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.