Primate Intelligence MCP vs Mediamcp

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.

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_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'.

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.

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.

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.