WavespeedMCP

WavespeedMCP is a Model Control Protocol (MCP) server that exposes WaveSpeed AI’s powerful image and video generation capabilities to any MCP‑compatible client, such as Claude Desktop. By wrapping the WaveSpeed API behind a standardized protocol, it removes the need for developers to write custom integration code and allows assistants to request high‑quality media directly from a single endpoint.

The server solves the common problem of fragmented AI media pipelines. Without MCP, developers must manage authentication, endpoint selection, file handling, and error recovery for each WaveSpeed service individually. WavespeedMCP consolidates these concerns into one configurable process: a single command‑line launch or environment‑variable configuration is enough to expose text‑to‑image, image‑to‑image, inpainting, and video generation as first‑class tools. This streamlines workflow creation, reduces boilerplate, and ensures consistent behavior across projects.

Key capabilities are delivered in plain language. Advanced image generation lets assistants produce high‑resolution images from natural‑language prompts, and even transform existing images with LoRA models or inpainting techniques. Dynamic video generation turns static visuals into motion, offering customizable speed and frame‑rate controls. The server tracks progress with intelligent polling and retry logic, giving clients precise status updates without manual intervention. Flexible resource handling supports output as URLs, local files, or Base64 strings, matching the needs of web services, desktop apps, or cloud functions. A comprehensive exception hierarchy and detailed logging make troubleshooting straightforward, while environment‑driven configuration keeps deployment painless.

Real‑world use cases abound. A content creator can embed WavespeedMCP in a script that automatically generates themed images for social media posts, while a game developer can generate concept art or animated cutscenes on demand. In research labs, AI assistants can prototype visual experiments by querying the server for rapid iterations of image or video samples. For developers building custom chatbots, integrating WavespeedMCP means the bot can respond to user prompts with freshly rendered media without exposing raw API keys or handling file uploads manually.

The integration flow is intentionally lightweight: after configuring the server via environment variables or a JSON snippet, any MCP client discovers the available tools through standard discovery messages. The client then invokes image or video generation by passing a prompt and optional parameters; the server forwards the request to WaveSpeed, polls for completion, and returns the result in the chosen format. This seamless loop keeps the AI assistant focused on conversation logic while offloading heavy media processing to WavespeedMCP, delivering a polished user experience with minimal overhead.