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WaveSpeed MCP Server

An MCP server for the WaveSpeed platform: run any model on the live catalog — image, video, audio, 3D — from Claude Code, Claude Desktop, Cursor, Cline, or any MCP client.

Built on the same design as the open-source @wavespeed/cli:

No hardcoded models for run_model. The catalog comes from the live API (1h cache); new platform models work the day they ship.
One general verb, five shortcuts. run_model executes anything; get_model_schema tells the agent what inputs a model actually accepts, so it reads before it writes. generate_image, edit_image, generate_video, edit_video and extend_video skip that: they use the same models as the WaveSpeed /chat page, pick the endpoint for what you give them and fit the request to its live schema.
Inputs are never mutated. The one explicit transform is the @path marker — a "@./photo.jpg" value inside input uploads the file and substitutes its hosted URL. Bare paths are passed through untouched. The shortcut tools (generate_image etc.) are the exception: they pick the endpoint and fit the request to the model, and report what they changed in notes.
Quote before you spend. get_price takes the same input as run_model and returns an estimate; the amount actually charged for a run is authoritative.

Tools

Tool	What it does
`list_models`	Search the live catalog by text or modality type
`get_model_schema`	A model's real input schema (required, properties, defaults), with a link to the model's playground page
`run_model`	Submit + wait; rejects input keys the model doesn't accept; `@path` inputs upload automatically; returns output URLs
`generate_image`	Image from a prompt with the /chat image models (default Seedream 5 Pro); reference images use the model's edit endpoint
`edit_image`	Edit, restyle or combine existing images with the same models
`generate_video`	Video from a prompt, a first/last frame or reference images/videos/audio, with the /chat video models (default Seedance 2.5); the mode (text, image, reference) is picked from the inputs
`edit_video`	Edit an existing video, optionally with reference images/audio
`extend_video`	Continue an existing video with new footage
`get_price`	Cost estimate for the inputs you pass (no charge), with a link to the model's playground page
`get_balance`	Account credit balance, with the top-up link
`list_predictions`	Run history (default last 24h); filter by model, status, time range
`list_billings`	Itemized charges and refunds (needs a Billing-access key)
`get_usage`	Spend, request counts and per-model breakdown (default last 7 days; needs a Billing-access key)
`delete_predictions`	Delete finished runs from the history (up to 100; needs `confirm: true`, cannot be undone from here)
`upload_file`	Local file → hosted URL (24h content-hash dedupe)
`get_prediction`	Status/outputs of any run by id; optional `wait_seconds` to wait for it

The five shortcut tools take wait_seconds like run_model, and estimate_only: true returns the price and the exact request that would run without submitting or charging anything. In their prompts, media is named @image 1, @video 1, @audio 1 (in the order given); it is renamed to what each model expects. Models and defaults follow /chat: an unknown model is rejected, and a named model is never switched.

Some generations take minutes to hours. run_model submits the run and returns the prediction id right away (done: false); the assistant then calls get_prediction with that id and wait_seconds (max 1800) until done is true. The task keeps running server-side, so a dropped connection loses nothing. Pass wait_seconds to run_model to wait for a quick model in the same call. While waiting, both tools send MCP progress notifications that carry the prediction id.

Setup

Remote (nothing to install)

The same server is hosted at:

https://api.wavespeed.ai/mcp

Claude on the web / ChatGPT: add a custom connector with that address and approve the connection on the WaveSpeed page that opens. Approving creates a dedicated API key (named MCP · <app>) that you can delete on the API Keys page to disconnect.
Claude Code: claude mcp add --transport http wavespeed https://api.wavespeed.ai/mcp
Cursor:
VS Code: code --add-mcp '{"name":"wavespeed","type":"http","url":"https://api.wavespeed.ai/mcp"}'
Any other client that sends request headers: point it at the URL with Authorization: Bearer <your API key>.

The hosted server has the same tools, with one difference for files: it cannot read files on your computer, so pass public URLs, use create_upload from a tool that can send HTTP requests (it returns a temporary upload address and the download_url to use as an input), or, in ChatGPT, attach the file to the chat (the upload_attachment tool, which only ChatGPT can fill, imports it and returns a download_url). Full guide: wavespeed.ai/docs/mcp.

Local (npx)

@latest makes npx fetch the newest release on each start; without it, npx runs a globally installed @wavespeed/mcp if one exists, however old.

Auth resolves from WAVESPEED_API_KEY, or from the CLI's stored login (wavespeed login) — one login covers both tools. Keys: wavespeed.ai/accesskey.

Claude Code

claude mcp add wavespeed -- npx -y @wavespeed/mcp@latest

Claude Desktop / other clients (mcpServers config):

{
  "mcpServers": {
    "wavespeed": {
      "command": "npx",
      "args": ["-y", "@wavespeed/mcp@latest"],
      "env": { "WAVESPEED_API_KEY": "wsk_..." }
    }
  }
}

Example prompts

"Generate a 16:9 hero image of a cyberpunk skyline at golden hour."
"Take ./photo.jpg and replace the background with a sunlit kitchen." (the agent passes "@./photo.jpg")
"Animate ./hero.png with subtle parallax — check the price first."

Development

npm install
npm run dev        # run from source (stdio)
npm run lint       # typecheck
npm run build      # tsc → dist/

License

MIT

WaveSpeed AI — AI image & video generation platform. Try it in the browser: Image generator · Video generator

mcp-server