AI image, video, and audio generation for MCP — one API key, every model, wiring never changes.
Most AI and media services work still happens through a UI a human drives. MediaEngine MCP server moves it into the conversation instead. AI image, video, and audio generation for MCP — one API key, every model, wiring never changes.
MCP server for MediaEngine — AI-powered image, audio, and video generation for Claude, Cursor, and other MCP clients.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
The server publishes 12 tools. What each one is for:
generate_image — Generate images from text prompts — full model catalog (Nano Banana, GPT-Image)generate_article_hero_image — Hero banner for blog posts and articlesgenerate_email_header_image — Header image for marketing emailsgenerate_social_teaser_image — Social media graphics for LinkedIn, Twitter, Instagramgenerate_video — AI video generation with provider-specific paramsgenerate_article_teaser_video — Short teaser videos from article contentgenerate_audio — Text-to-speech synthesisgenerate_article_narration — Audio narration for articles and blog postswait_for_job — Poll until a media job completesget_job_status — Check status of a media joblist_jobs — List media jobs with filtering and paginationCursor — The Cursor tool exposed by this serverConfiguration is passed through the environment: MEDIAENGINE_BASE_URL, MEDIAENGINE_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. MediaEngine's toolset — generate_image, generate_article_hero_image, generate_email_header_image and 9 more — is a fair guide to whether it matches your workflow. It is maintained by Tr1ckyMag1ca1; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| generate_image | Generate images from text prompts — full model catalog (Nano Banana, GPT-Image) |
| generate_article_hero_image | Hero banner for blog posts and articles |
| generate_email_header_image | Header image for marketing emails |
| generate_social_teaser_image | Social media graphics for LinkedIn, Twitter, Instagram |
| generate_video | AI video generation with provider-specific params |
| generate_article_teaser_video | Short teaser videos from article content |
| generate_audio | Text-to-speech synthesis |
| generate_article_narration | Audio narration for articles and blog posts |
| wait_for_job | Poll until a media job completes |
| get_job_status | Check status of a media job |
| list_jobs | List media jobs with filtering and pagination |
| Cursor | The Cursor tool exposed by this server. |
{
"mcpServers": {
"mediaengine": {
"command": "npx",
"args": ["-y", "mcp-media-engine"],
"env": {
"MEDIAENGINE_BASE_URL": "https://your-mediaengine-instance.com",
"MEDIAENGINE_API_KEY": "your-api-key"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| MEDIAENGINE_BASE_URL | Endpoint or connection string the server talks to. | Yes |
| MEDIAENGINE_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.