vMix MCP Server

MCP vMix Server – Bringing Live Video Control into AI Workflows

The mcp-vmix server is an experimental bridge that exposes the full feature set of vMix, a popular live‑production software, to AI assistants via the Model Context Protocol. By turning vMix into a programmable resource, developers can let language models orchestrate live video mixing, camera switching, and effect application in real time. This solves the problem of tightly coupling creative video production to manual control, enabling AI‑driven automation and intelligent assistants that can manage broadcasts without human intervention.

At its core, the server offers a collection of resources that represent vMix’s components: scenes, inputs, transitions, and effects. Each resource is described by a schema that maps vMix’s API into MCP terminology, allowing an AI client to query the current state (e.g., “which input is on screen?”) and issue commands (“switch to Input 3 with a fade transition”). The server translates these high‑level requests into the native vMix commands, ensuring seamless operation. This abstraction lets developers treat video mixing as a first‑class data source in the same way they might query weather or database services.

Key capabilities include:

• Real‑time state introspection – Retrieve the current mix layout, active inputs, and transition settings.
• Command execution – Trigger camera cuts, apply transitions, adjust audio levels, and launch macros.
• Event streaming – Subscribe to vMix events (e.g., input added, transition finished) so AI agents can react instantly.
• Prompt customization – Pre‑define prompts that encapsulate common production tasks, making it easier for an assistant to understand and execute complex workflows.

Typical use cases span live streaming, webinar production, and automated broadcast control. For example, a virtual event platform could let an AI host manage the show’s pacing: “When the speaker finishes, switch to a pre‑recorded thank‑you video.” In a newsroom, an assistant could monitor incoming footage and automatically switch to the most relevant camera feed based on keyword detection in captions. Because MCP servers are stateless and interoperable, the same AI model can integrate mcp-vmix alongside other services—like audio processing or data feeds—without rewriting logic.

What sets this server apart is its experimental nature: it pushes the boundaries of how live media can be treated as programmable data. By exposing vMix’s full command set through MCP, developers gain unprecedented flexibility to blend human creativity with AI automation. Whether building a hands‑free studio controller or a responsive event host, mcp-vmix opens the door to intelligent video production that was previously limited to manual operation.