check_config
Diagnose the mediamcp server setup: endpoint, API key presence and validity, default models, and output directory writability. Run this first when any other mediamcp tool fails.
LABSCO SUMMARY
Image and video generation with the file on disk and the path in the reply.
Saving every result and returning its absolute path is what makes it composable — the next tool in the chain can open the file rather than re-deriving it. Video is asynchronous by nature, so check_video_status exists to pick a job back up rather than holding a call open for minutes; check_config is the first thing to run when something misbehaves.
What it is
An MCP server that connects an assistant to cloud image and video models — Gemini Flash Image, GPT-5 Image, Seedream, Veo, Sora and others — through OpenRouter or any OpenAI-compatible API. Every generated file is written to disk and the response carries its absolute path plus a small inline preview, so the agent can see what it produced.
What you get
- generate_image — one or more images from a text prompt, each saved to disk with its path and a preview returned
- edit_image — transform existing images with an instruction: restyle, add or remove elements, change the background, or combine several into one scene
- generate_video — video from a prompt, optionally starting from an input image; an async job that starts generation and then polls, typically taking minutes
- check_video_status — resume a started job from its polling URL or video id, download the finished video and return its path
- list_models — the image- and video-capable model slugs available on the configured endpoint, with pricing where known
- check_config — diagnose the setup: endpoint, key presence and validity, default models and whether the output directory is writable
Requirements
An OpenRouter API key in OPENROUTER_API_KEY, or any OpenAI-compatible endpoint. Clients run npx -y mediamcp over stdio; Node.js 20 or newer. MEDIAMCP_OUTPUT_DIR sets where files land (default ~/Pictures/mediamcp) and MEDIAMCP_MODEL sets the default image model (google/gemini-2.5-flash-image). The README is written in Russian, with an English version alongside it.
Setup effort
One command plus a key — claude mcp add mediamcp -e OPENROUTER_API_KEY=<YOUR_OPENROUTER_API_KEY> -- npx -y mediamcp
USE CASES
01
Producing an illustration for a document
Generate from a prompt and get the file path back to drop into the page.
02
Fixing an image you already have
Restyle it, remove an element, or merge several references into one scene.
03
Making a short clip
Start the generation, then pick the job back up when it finishes and download the file.
04
Choosing a model for the job
List what the endpoint offers with pricing, then set it as the model for the call.
05
Working out why nothing is generating
Check the endpoint, key validity, default models and output directory in one call.
6 tools
Counted once with only startup setup. Other versions, modes or optional credentials may expose a different list.
check_video_status
Check a previously started video generation job (from generate_video's polling_url or video id). If the job has completed, downloads the video, saves it to disk, and returns the absolute path.
edit_image
Edit or transform existing image(s) with a text instruction — restyle, add or remove elements, change background, or combine several images into one scene. The result is saved to disk and its absolute path is returned, along with a small inline preview.
generate_image
Generate one or more images from a text prompt using a cloud AI model. Every image is saved to disk and its absolute path is returned, along with a small inline preview. Use edit_image instead when starting from an existing image.
generate_video
Generate a video from a text prompt, and optionally from an input image (image-to-video). Async job: starts generation, then waits and polls. Video generation typically takes 1-5 minutes. The finished file is saved to disk and its absolute path is returned. If waiting times out, a polling_url is returned — pass it to check_video_status later instead of starting a new (billed) job. For image-to-video, pass first_frame_image so the clip animates from that exact picture (e.g. a still produced by generate_image). Image inputs require an image-to-video-capable model such as 'bytedance/seedance-2.0', 'bytedance/seedance-2.0-fast', or 'google/veo-3.1'.
list_models
List image- and video-capable model slugs available on the configured endpoint, with pricing where known. Use this to pick a model value for generate_image, edit_image, or generate_video.
BEFORE YOU INSTALL
What to know first
Tools you get
6 tools when we connected.
Requires
- npx on PATH
- OPENROUTER_API_KEY in your environment
Where it runs
All 5 documented clients run the server on your machine.
CONTEXT COST
Light Standing cost
Rated by the size of the 6 tool definitions that ride along on every turn, not by how many there are
INSTALLATION
Connect your client
Server setup
Claude Code
TERMINAL
claude mcp add mediamcp -e OPENROUTER_API_KEY=<YOUR_OPENROUTER_API_KEY> -- npx -y mediamcpMCP Clients
Claude Desktop, Cursor, Windsurf
JSON
{
"mcpServers": {
"mediamcp": {
"command": "npx",
"args": [
"-y",
"mediamcp"
],
"env": {
"OPENROUTER_API_KEY": "<YOUR_OPENROUTER_API_KEY>"
}
}
}
}VS Code
VS CODE · JSON
{
"servers": {
"mediamcp": {
"command": "npx",
"args": [
"-y",
"mediamcp"
],
"env": {
"OPENROUTER_API_KEY": "${input:openrouter-key}"
}
}
},
"inputs": [
{
"id": "openrouter-key",
"type": "promptString",
"password": true,
"description": "OpenRouter API key (https://openrouter.ai/keys)"
}
]
}
