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mediagen

AI image and video generation skill for Claude Code and other coding agents — Gemini, OpenAI and Kie AI behind one CLI and MCP server, with EU AI Act content marking.

Install / Use

claude mcp add Cripacx -- npx -y github:Cripacx/mediagen

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

87/100

Supported Platforms

Claude Code
Claude Desktop
Gemini CLI

Our assessment of mediagen

mediagen scores 87/100 on our quality scale, 2042nd of 4,625 Development & Engineering skills we index (top 45%).

Its MCP Server is 17 KB long, well organised into 14 sections with 20 code examples: a thorough specification that gives an agent plenty to work with.

It has 50 GitHub stars, a meaningful sign that others use it.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
7/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 30 days ago, so mediagen is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-11-06. Automated pattern scan on 2026-11-06. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

mediagen compared with similar skills

All 4 of these similar skills score higher than mediagen; compare them before choosing.

SkillScoreStarsUpdatedFormat
mediagen (this skill)by Cripacx875030d agoMCP Server
taste-skillby Leonxlnx100111.2k2d agoCLAUDE.md
Agent-Reachby Panniantong100109.6ktodayCLAUDE.md
headroomby headroomlabs-ai10079.0ktodayCLAUDE.md
ai-job-searchby ai-job-search-dev10070.1k1d agoCLAUDE.md

Frequently asked questions

How do I install mediagen?
Run claude mcp add Cripacx -- npx -y github:Cripacx/mediagen. The install tabs above show the steps for each supported agent.
Which AI agents does mediagen work with?
It is written for Claude Code, Claude Desktop and Gemini CLI, as a MCP Server file. Other agents that read the same format can often use it too.
Is mediagen safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is mediagen still maintained?
The repository was last updated 30 days ago, so mediagen is actively maintained.

mediagen — an image and video generation skill for coding agents

npm CI node

Give your agent image and video generation across Google Gemini, OpenAI and Kie AI — one skill, one install, no API to learn.

Say roughly what you want and let it decide the rest:

You:   Make a hero image for the landing page, wide, something moody and industrial.

Agent: npx -y mediagen image "A disused loading dock at dusk, wet concrete…"
         --aspect-ratio 21:9 --json
       → ./output/image-20260823T094107Z.png

It wrote the prompt out in full, knew 21:9 rules OpenAI out, and read the path back from --json.

Or be exact, and it stops deciding:

You:   Same thing with gemini-3-pro-image, 21:9, 4K, marked as AI-generated,
       saved as hero.png.

Agent: npx -y mediagen image "A disused loading dock at dusk, wet concrete…"
         --model gemini-3-pro-image --aspect-ratio 21:9 --size 4K
         --output-name hero.png --json
       → ./output/hero.jpg

       [looks at the image]

       npx -y mediagen mark ./output/hero.jpg --visible-label
         --label-position top-right --json
       → ./output/hero.labelled.jpg

It marked in a second pass, after seeing where the subject ended up — and put the label on the flat roofline rather than over the loading bay.

Anything the CLI takes can be asked for in words — provider, model, aspect ratio, size, output name and directory, quality preset, video duration, an input image to edit, and whether to mark the result. Name any of them and the agent uses it as given; leave it out and it chooses, or falls back to what you configured.

Install

npx -y skills add Cripacx/mediagen --skill mediagen

That is the whole installation. Nothing else to set up — the skill runs the CLI through npx, which fetches it on first use and caches it afterwards.

Then give it a key:

npx -y mediagen init

An interactive wizard: pick providers, enter each key without it being echoed, verify each against the live API, choose a model per provider, and set a default. One key is enough to start.

Now just ask your agent for an image.

What your agent can do with it

  • Generate images and video from a description, or edit media you already have
  • Choose the right provider for the task — the skill knows Gemini handles 21:9 and video, that OpenAI cannot do 16:9 at all, and that Kie aggregates around thirty third-party models
  • Take your instructions literally when you give them. Name a model, a ratio, a size or a filename and it is used as stated. mediagen models is there when you want to see what is available before choosing
  • Write the prompt properly. The skill carries prompt-writing guidance, so "a hero image, moody and industrial" becomes a full description of subject, composition, light, camera and materials before anything is sent
  • Mark AI-generated output when it matters — the skill suggests it for anything photorealistic or destined for publication
  • Recover from failures on its own, because every error carries a machine-readable code and a next action

And what it will not do: ask you to paste an API key into the chat. On a configuration error the skill tells you to run mediagen init in your own terminal.

Prerequisites

  • At least one API key:
  • Node.js 20.11 or later

Configuration

mediagen init covers first-time setup. To change something later:

npx -y mediagen config edit

A menu of every setting with its current value and where that value came from — provider, model, key, output directory, quality preset, and what mediagen mark does by default. Each change is written as you make it.

For CI and scripts, where there is no terminal, config set takes the same settings as arguments:

echo "$GEMINI_API_KEY" | npx -y mediagen config set gemini --stdin
npx -y mediagen config set gemini-model gemini-3-pro-image

Which provider gets used

Set the order you prefer, most preferred first:

npx -y mediagen config set provider-priority gemini,kie,openai

It is a preference, not a whitelist. A request with no --provider goes to the first provider in the order that has a key and can do the job — so a missing OpenAI key never stops something Gemini can do, and asking for video skips straight past the providers that do not make any. Naming --provider overrides all of it.

mediagen models shows the resulting order, which providers are usable, and what a request would get:

1. Google Gemini (gemini)  [preferred, key from config file]
  Would use: gemini-3.1-flash-image  (provider default)
2. Kie AI (kie)  [key from config file]
3. OpenAI (openai)  [preferred, no key]
  No key configured, so requests to it fail. Fix: mediagen config set openai

A request with no --provider uses gemini/gemini-3.1-flash-image.

With --json it adds wouldUse, usableProviders and providerPriority. That is what the skill has an agent read before generating, so it never picks a model from a provider you have no key for.

To check what is configured and whether the keys still work:

npx -y mediagen doctor

doctor reports, per provider, whether a key is configured, which layer it came from, and whether the provider accepts it — keeping not configured, rejected, unreachable and no cheap way to check distinct, because they call for four different fixes.

[!WARNING] There is deliberately no flag that takes an API key as an argument. Arguments land in shell history and in the process list, where they outlive the command that used them.

Settings resolve from the environment first, then .env in the working directory, then the config file:

| Variable | Purpose | | ------------------------------------------------- | ------------------------------ | | GEMINI_API_KEY, OPENAI_API_KEY, KIE_API_KEY | credentials; at least one | | MEDIAGEN_PROVIDER_PRIORITY | providers in preference order | | GEMINI_MODEL, OPENAI_MODEL, KIE_MODEL | default model per provider | | MEDIAGEN_OUTPUT_DIR | where media is saved | | MEDIAGEN_QUALITY | fast, balanced, quality | | MEDIAGEN_MARK | mark output by default | | MEDIAGEN_VISIBLE_LABEL | add a visible label by default |

[!TIP] A stale environment variable shadowing the key you just configured is the most expensive failure this kind of tool has. mediagen config list marks every shadowed value, so you can see it rather than guess.

Providers

| Provider | Images | Video | Editing | Key verification | | ----------------- | ------------------------------ | ----- | ------- | -------------------------------- | | Google Gemini | Nano Banana family, up to 4K | yes | yes | live probe | | OpenAI | gpt-image family, DALL·E | — | yes | live probe | | Kie AI | ~30 models: Flux, Imagen, Grok | — | most | no cheap probe; reported as such |

[!NOTE] OpenAI takes pixel dimensions rather than aspect ratios and genuinely cannot produce 16:9 — its widest image is 1536×1024, which is 3:2. Asking for 16:9 is refused by name rather than quietly served as something else. The skill knows this and routes wide shapes to Gemini.

A model absent from the listings is still sent to the provider, so a newly released model works before mediagen knows about it. Kie's catalogue is generated from Kie's own documentation rather than maintained by hand.

Content marking

The EU AI Act splits disclosure into two duties, so mediagen mark has two independent switches:

| Flag | Duty | What it does | | ----------------- | ------------------------- | -------------------------------------------------- | | machine-readable | make it findable by tools | writes IPTC/XMP DigitalSourceType, on by default | | --visible-label | disclose it to people | composites the EU's official AI-content label |

Generating never marks. Marking is always a second command, run on the file afterwards:

npx -y mediagen image "a wide banner" --aspect-ratio 21:9 --size 2K --json
npx -y mediagen mark ./output/image-….jpg --visible-label --label-position top-left

That is not ceremony. A visible label has to go where the subject is not, and only the finished image can say where that is. The machine-readable marker is not free either: adding metadata to a JPEG or WebP means decoding and re-encoding it, so marking costs a second lossy pass — worth paying deliberately, not as a side effect of asking for an image. mediagen re-encodes at high quality to keep that cost small, but it cannot make it zero.

To have mediagen mark draw the visible label without being asked each time:

npx -y mediagen config edit      # "AI marking by default"

A configured default is still overridable per run with --no-mark or --no-visible-label.

The visible label is the European Commission's own icon, published with the Code of Practice on Transparency of AI-generated Content and free to use without attribution. Two of its three variants are used: AI GENERATED by default, AI MODIFIED with --modified, for media a person made and a model altered. The light or dark version is picked from what is actually under the corner it lands in, because a label nobody can read is not a disclosure.

It sits bottom-right by default. --label-position moves it to another corner, or auto puts it wherever the image has the least detail.

[!IMPORTANT] A visible label is never written over its source. mediagen mark photo.png --visible-label produces photo.labelled.png and leaves the pixels of photo.png exactly as they were, while writing the machine-readable marker into it — so whichever of the two you publish carries the disclosure. A label placed badly can be redone from an untouched original and from nothing else. --in-place overwrites if you really mean to.

Using it without an agent

The skill is a wrapper around a CLI, and the CLI stands on its own.

npx -y mediagen image "a wide banner" --aspect-ratio 21:9 --size 2K
npx -y mediagen image "make the sky stormy" --input ./photo.jpg
npx -y mediagen mark ./output/image-….jpg --visible-label
npx -y mediagen video "a marble rolling down a wooden track" --duration 6
npx -y mediagen models

Install it globally if you use it often enough to want the shorter command:

npm install -g mediagen

Options

| Option | | | ------------------------ | ----------------------------------- | | --provider <name> | gemini, openai, kie | | --model <id> | see mediagen models | | --input <path> | source media to edit or transform | | --aspect-ratio <ratio> | 1:1, 16:9, 9:16, … | | --size <size> | 1K, 2K, 4K | | --duration <seconds> | video only | | --output-name <name> | the

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars50
CategoryDevelopment
Updated1mo ago
Forks0

Languages

TypeScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions
mediagen — MCP Server: Install & Safety Check | SkillAgent