VseGPT MCP Server

Overview of the VseGPT MCP Servers

The VseGPT MCP servers provide a modular, Python‑based bridge between the VseGPT platform and language models that speak the Model Context Protocol (MCP). By exposing dedicated services for image generation and text‑to‑speech, they enable AI assistants to request up‑to‑date visual or auditory content without hardcoding the logic into the model itself. This decoupling keeps the model’s prompt lean while still offering rich, dynamic capabilities.

The image generation server () accepts a prompt and forwards it to the VseGPT image API. It automatically stores the resulting file in a local directory and returns a URL or path that the model can use. The text‑to‑speech server () works similarly, but instead of returning a static file it triggers the MPC‑HC player to play the synthesized audio in real time. Both services rely on a single required environment variable, , ensuring secure authentication with the VseGPT backend.

For developers, this architecture offers several practical advantages. First, each capability lives in its own server, so a model can dynamically enable or disable tools by simply adding or removing the corresponding MCP endpoint. This keeps the tool list concise and prevents the model from being overwhelmed by irrelevant options. Second, because the servers expose a standardized MCP interface, any language model that understands MCP can tap into them without needing custom adapters. Finally, the servers are lightweight; they run on and can be launched with a single command, making them ideal for rapid prototyping or production deployments.

Typical use cases include generating illustrative images for content creation, creating voice‑over narration for videos or podcasts, and building interactive chatbots that can produce multimedia responses on demand. In a marketing workflow, for example, an AI assistant could ask the image server to create a banner design and immediately embed it in an email template. In educational settings, the TTS server could read out explanations or provide accessibility support.

Overall, the VseGPT MCP servers turn the VseGPT API into a flexible toolkit that can be composed on demand, allowing developers to enrich their AI assistants with real‑world actions while maintaining clean, manageable prompts.