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MCP for kie.ai: 45+ image, 70+ video, 20+ audio models with model intelligence
MCP for kie.ai: 45+ image, 70+ video, 20+ audio models with model intelligence
This MCP server is a well-structured API wrapper for kie.ai's generative models with proper authentication requirements and reasonable permissions for its intended purpose. However, there are moderate concerns around filesystem path handling, error handling practices, and input validation that should be addressed. The server requires API key authentication and has appropriate scope limitations, but lacks defensive programming in several areas. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
3 files analyzed · 10 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: KIE_API_KEY
Environment variable: KIE_PROJECT_ROOT
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-elibarnett-kie-mcp": {
"env": {
"KIE_API_KEY": "your-kie-api-key-here",
"KIE_PROJECT_ROOT": "your-kie-project-root-here"
},
"args": [
"-y",
"kie-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
A comprehensive Model Context Protocol server for the kie.ai generation API. Gives Claude (and any MCP client) access to 45+ image models, 70+ video models, and 20+ audio tools with deep model intelligence built in.
Most MCPs are thin API wrappers. This one is different:
research field with verdicts, prompt techniques, weaknesses, cost-efficiency analysis, and competitor comparisons. Researched by Averiguare, our model intelligence agent.list_models filter="lip sync" or filter="architecture" or filter="cheapest video" — searches across capability tags, descriptions, AND research fields.Just ask Claude things like:
git clone https://github.com/YOUR_USERNAME/kie-mcp.git
cd kie-mcp
npm install
Add to your Claude config (~/.claude.json for Claude Code, or your MCP client's equivalent):
{
"mcpServers": {
"kie-art": {
"command": "node",
"args": ["/absolute/path/to/kie-mcp/server.mjs"],
"env": {
"KIE_API_KEY": "your-kie-ai-api-key",
"KIE_PROJECT_ROOT": "/optional/path/for/outputs"
}
}
}
}
Or use the Claude Code CLI:
claude mcp add -s user kie-art /usr/bin/env -- KIE_API_KEY=your-key node /path/to/server.mjs
KIE_API_KEY=your-key node server.mjs --http --port=3100
Then expose via ngrok / Cloudflare Tunnel / VPS deployment:
ngrok http 3100
Configure your MCP client to use the resulting URL:
{
"mcpServers": {
"kie-art": {
"type": "http",
"url": "https://your-tunnel.ngrok-free.dev/mcp"
}
}
}
| Variable | Required | Purpose |
|---|---|---|
KIE_API_KEY | yes | Your kie.ai API key |
KIE_PROJECT_ROOT | no | Where generated files are saved (default: current working dir). Files go to $KIE_PROJECT_ROOT/kie/assets/raw/ |
KIE_MCP_PORT | no | Port for HTTP mode (default: 3100) |
generate_image, generate_video, generate_music, generate_sfx,
generate_tts, generate_dialogue, generate_sounds, generate_lyrics,
generate_persona, generate_mashup, generate_cover_art,
generate_midi, create_music_video,
extend_music, cover_audio, upload_extend_audio,
add_instrumental, add_vocals, replace_section,
convert_to_wav, separate_vocals, boost_style,
get_timestamped_lyrics, audio_isolation, speech_to_text,
list_models, check_task, list_tasks, check_credits,
download_result, list_raw_assets, upload_file,
veo_extend, veo_upscale_1080p, veo_upscale_4k, runway_extend
Try these queries in any MCP client:
list_models filter="reasoning" # GPT-4o, Nano Banana, GPT Image 2
list_models filter="lip-sync" # Kling Avatar, Infinitalk, Wan Speech
list_models filter="multi-shot" # Kling 3.0, Sora Storyboard
list_models filter="cheapest video" # Wan Flash, Sora 2 standard
list_models filter="alibaba" # HappyHorse 1.0 family
list_models filter="best visual quality" # Veo Quality, Seedance 2.0
list_models filter="text rendering" # Ideogram v3, GPT Image 2
list_models filter="character" # Sora Characters, Ideogram Character
server.mjs # The whole server (~4000 lines)
├── PRICING # Credit cost per model
├── MODEL_REGISTRY # Image models (45+)
├── VIDEO_MODEL_REGISTRY # Video models (70+)
├── AUDIO_TOOLS_REGISTRY # Audio tool metadata
├── createMcpServer() # Factory for stdio + HTTP modes
└── Tool handlers # generate_*, list_*, etc.
Each model entry has:
name, description, capabilities (tags), pricing (credits)aspectRatios, options (with types and defaults)buildBody / buildInput (request builders)research (Averiguare verdicts, prompt techniques, weaknesses, comparisons, sources)MIT
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