WOF Utilization MCP Server

Overview

The Wof Utilization MCP Server provides a lightweight, high‑performance interface for retrieving real‑time occupancy data from WOF (Workout of the Future) gym facilities. By exposing this information through the Model Context Protocol, AI assistants can query current utilization levels without needing direct access to proprietary gym APIs or databases. This enables developers to build context‑aware fitness applications, chatbots, and scheduling tools that react instantly to the state of a gym.

Problem Solved

Many fitness platforms and personal assistants lack reliable, up‑to‑date knowledge of gym capacity. Users often face long wait times or must manually check websites, leading to frustration and missed workout opportunities. The MCP server solves this by aggregating sensor data (e.g., door counters, occupancy sensors) from WOF gyms and presenting it via a standardized protocol. Developers can therefore deliver instant, accurate capacity insights to end‑users.

Core Functionality

• Real‑time Utilization Queries: Clients can request the current number of occupants or percentage capacity for any WOF gym. The server returns concise, machine‑readable data that can be incorporated into AI responses.
• Historical Trend Access: Optional endpoints expose aggregated usage patterns over time, allowing predictive analytics or trend‑based recommendations.
• Secure, Rate‑Limited Access: The server enforces API keys and throttles requests to protect gym infrastructure while ensuring consistent availability for AI assistants.

Value to Developers

By integrating this MCP server, developers can enrich their AI‑powered fitness solutions with instant context about gym availability. This eliminates the need to build custom scrapers or maintain separate data pipelines, reducing development time and operational overhead. The server’s adherence to MCP standards guarantees seamless compatibility with any Claude or other AI assistant that supports the protocol.

Real‑World Use Cases

• Personal Fitness Assistants: A chatbot can advise a user to join the nearest WOF gym if it’s under capacity, or suggest an alternative location when a particular studio is full.
• Scheduling & Reservation Systems: Applications can automatically book slots only when the gym has available capacity, preventing double bookings.
• Operational Analytics: Gym managers can expose utilization data to AI agents that monitor traffic patterns and trigger maintenance alerts or staffing adjustments.

Unique Advantages

Unlike generic occupancy APIs, this server is tailored specifically for WOF gyms, ensuring that data formats and terminology match the brand’s ecosystem. Its tight integration with MCP means developers can invoke utilization checks directly within AI prompts, enabling truly conversational experiences where the assistant dynamically references live gym conditions. Additionally, the server’s lightweight .NET implementation guarantees low latency and high scalability, making it suitable for both small startups and large enterprise deployments.