kie-mcp

A comprehensive Model Context Protocol server for the kie.ai generation API. Gives Claude (and any MCP client) access to 54+ image models, 95+ video models, and 20+ audio tools with deep model intelligence built in.

Why this exists

Most MCPs are thin API wrappers. This one is different:

• Vertical profiles (NEW in 5.0) — per-domain playbooks: profile_brief returns the intake questions a professional would ask, model routing per deliverable with live costs, per-model prompt formulas, and multi-tool workflows. Profiles double as MCP prompts (/kie-art:architecture in Claude Code). Verticals (10): architecture & interiors, video game assets, advertising & marketing, web & software product imagery, film & storyboarding, product photography & e-commerce, brand & graphic design, editorial & publishing, short-form social video, and audio branding & music.

• Deep research embedded — Every major model has a research field with verdicts, prompt techniques, weaknesses, cost-efficiency analysis, and competitor comparisons. Researched by Averiguare, our model intelligence agent.

• Cost-aware — Every model has pricing in credits and USD. The MCP tells you the cheapest option for your use case.

• Smart filtering — list_models filter="lip sync" or filter="architecture" or filter="cheapest video" — searches across capability tags, descriptions, AND research fields.

• Dual-mode transport — stdio for local Claude Code, HTTP Streamable for remote Cowork/cloud usage.

What you can do with it

Just ask Claude things like:

• "Generate a brand presentation board for a perfume launch" — picks GPT Image 2 (best for text-heavy layouts)
• "Make a 10s video of fruit scarecrows defending against crows, Pixar style" — recommends Veo 3.1 or Wan 2.7
• "Generate music for a fantasy adventure game" — Suno V5
• "Lip-sync this audio to my character image" — Kling AI Avatar or Infinitalk
• "Upscale this video to 4K" — Veo 4K upscale or Topaz
• "Replace the wall color in this room photo" — Flux Kontext Pro (best for surgical edits)

Model coverage

Image (54+)

• OpenAI: GPT Image 2 (NEW), GPT-4o Image, GPT Image 1.5
• Google: Nano Banana 2 / 2 Lite (NEW) / Pro / Edit / Original, Imagen 4 (Fast/Standard/Ultra)
• Black Forest Labs: Flux Kontext Pro/Max, Flux 2 Pro/Flex
• ByteDance: Seedream 3.0 / 4.0 / 4.5 / 5.0 Lite
• Alibaba: Wan 2.7 Image / Image Pro
• Ideogram: v3, Character, Edit, Remix, Reframe
• xAI Grok Imagine Image 2.0 (#2 Arena T2I + edit; free segment map → region-targeted edit chain; whole-image edits of ANY uploaded image)
• ByteDance Seedream 5.0 Pro (NEW — T2I/I2I + layer decomposition: split any image into layer files)
• Qwen Image 3.0 / 3.0 Pro (NEW — seed, negative prompts, 2K at the 1K price on standard)
• Others: Qwen/Qwen2, Z-Image, Grok Imagine 1.x, Recraft, Topaz

Video (95+)

• Google Veo 3.1: Quality / Fast / Lite (T2V + I2V), Extend, 1080p/4K upscale
• Alibaba HappyHorse: 1.1 (NEW — T2V/I2V/R2V with native audio + 7-language lip-sync), 1.0 (T2V/I2V/R2V/Video Edit)
• ByteDance Seedance: 2.5 (NEW — 30s single takes, live Aug 2026) / 2.0 / 2.0 Fast / 2.0 Mini / 1.5 Pro
• Kuaishou Kling: 3.0 Omni "O3" (NEW — per-shot multi_prompt scripting, 4K, video Transformation), 3.0, 3.0 Turbo, 2.6, V2.5 Turbo, V2.1 Master/Pro/Standard, AI Avatar
• Alibaba Wan: 3.0 + 3.0 Prime (NEW — unified prompt-or-media, audio), 2.7 (T2V/I2V/Edit/R2V), 2.6, 2.5, 2.2 Turbo, Animate
• MiniMax Hailuo: H3 (NEW — 2K + native stereo audio, image+video+audio references, first→last-frame I2V), 2.3 Pro/Standard, 02 Pro/Standard
• xAI Grok Imagine: Video 1.5 preview (NEW — I2V with native audio, cheapest audio video), T2V, I2V, Upscale, Extend
• Avatar / lip-sync: OmniHuman 1.5 (NEW — audio-driven full-body avatar + free subject-detection utility), Volcengine Video Lip-Sync (NEW — re-dub existing footage), Kling AI Avatar, Infinitalk
• PixVerse V6 (NEW): T2V, I2V (viral templates), Transition (first→last morph), Fusion R2V (@ref_name), Extend — budget all-rounder with native audio
• Runway: Aleph, Aleph Edit, Extend
• Others: ByteDance V1 Pro/Lite, Topaz upscale

Audio (20+)

• Suno: Music Gen, Extend, Cover, Add Instrumental/Vocals, Replace Section, Lyrics, Sounds, Sound Effects, MIDI, Music Video, Cover Art, Mashup, Persona, Timestamped Lyrics, Boost Style, Vocal Separation, WAV, Custom Voice cloning (experimental)
• ElevenLabs: TTS (Turbo 2.5 + Multilingual V2), Text-to-Dialogue V3, Audio Isolation, Speech-to-Text
• Google Gemini TTS (NEW): style-directed speech, 30 voices, 2-speaker dialogue, inline tone tags — ~4.2 cr/min

Utility

• File upload (URL or base64)
• Veo Extend, 1080p Upscale, 4K Upscale
• Runway Extend
• Task status, credit check, raw asset listing

Installation

Prerequisites

• Node.js 18+
• A kie.ai API key from kie.ai/api-key

Setup

git clone https://github.com/YOUR_USERNAME/kie-mcp.git
cd kie-mcp
npm install

Run as stdio MCP (Claude Code, Claude Desktop)

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

Run as HTTP MCP (Cowork, remote clients)

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"
    }
  }
}

Environment variables

| Variable | Required | Purpose | |---|---|---| | KIE_API_KEY | yes | Your kie.ai API key | | KIE_PROJECT_ROOT | no | Server-wide default for where generated files are saved (default: server cwd; files go to $KIE_PROJECT_ROOT/kie/assets/raw/). Per-call download_dir (absolute path) on any file-writing tool overrides this | | KIE_MCP_PORT | no | Port for HTTP mode (default: 3100) | | KIE_CALLBACK_URL | no | Callback URL sent with Suno generation requests (kie.ai requires the field; results are fetched by polling regardless). Defaults to an inert placeholder — set this only if you want to receive the callbacks yourself | | KIE_MAX_CONCURRENT | no | Max simultaneous task-creation calls (default 4). Excess parallel generations queue inside the server instead of hitting kie.ai's rate limits — parallel tool calls are safe | | KIE_POLL_BUDGET_IMAGE / _VIDEO / _AUDIO / _SPEECH | no | Blocking-mode polling budget per tool category, in seconds (defaults: 600 / 900 / 300 / 300). Per-call max_wait_seconds takes precedence. For long generations prefer wait: false (async mode): the tool returns the task_id immediately; poll with check_task, fetch with download_result |

Tools available

generate_image, generate_video, generate_music, generate_sfx,
generate_tts, generate_gemini_tts, generate_dialogue, generate_sounds, generate_lyrics,
generate_persona, generate_mashup, generate_cover_art,
generate_midi, create_music_video,
prepare_voice_clone, create_voice_clone, regenerate_voice_clone,
create_omni_voice, create_omni_character,
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,
profile_brief,
list_models, check_task, list_tasks, check_credits,
download_result, list_raw_assets, upload_file,
grok_segment_map, grok_image_edit, seedream_layer_decompose,
veo_extend, veo_upscale_1080p, veo_upscale_4k, runway_extend

Smart model recommendations

Try these queries in any MCP client:

list_models filter="reasoning"          # GPT-4o, Nano Banana, GPT Image 2
list_models filter="lip-sync"           # OmniHuman 1.5, Volcengine, Kling Avatar, HappyHorse 1.1
list_models filter="multi-shot"         # Kling 3.0/Turbo
list_models filter="cheapest video"     # Grok Imagine 1.5, Wan Flash
list_models filter="alibaba"            # HappyHorse 1.0/1.1 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"          # Ideogram Character, Kling AI Avatar

Architecture

server.mjs                      # Transport, helpers, tool handlers (~2700 lines)
├── createMcpServer()           # Factory for stdio + HTTP modes
├── Tool handlers               # generate_*, list_*, etc.
└── helpers                     # polling, recovery, pricing, validation, download

data/                           # Pure data, imported (and re-exported) by server.mjs
├── registry-image.mjs          # MODEL_REGISTRY — image models (47+)
├── registry-video.mjs          # VIDEO_MODEL_REGISTRY — video models (80+)
├── registry-audio.mjs          # AUDIO_TOOLS_REGISTRY — audio tool metadata
├── pricing.mjs                 # PRICING, PRICING_ESTIMATED, PROMPT_CAPS
└── voices.mjs                  # ELEVENLABS_VOICES catalog

The registries and pricing live in data/*.mjs so model-catalog changes are reviewable diffs instead of edits buried in a 5000-line file; server.mjs imports and re-exports them (tests and downstream keep importing from server.mjs).

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)

Development

npm run check   # node --check server.mjs (syntax)
npm test        # offline unit tests for the pure helpers (test/*.test.mjs)
npm run smoke   # live end-to-end over MCP stdio — needs KIE_API_KEY
                # (spends ~0 credits; uses the free subject-detection model)

server.mjs guards its side effects behind a main-module check, so it can be imported by tests (test/unit.test.mjs) to exercise the pure helpers without starting a server. test/harness.mjs is a reusable stdio JSON-RPC client for driving the real server in smoke/integration checks. CI (.github/workflows/ci.yml) runs the syntax check + unit tests on Node 20 and 22 for every push and PR.

Drift watch

kie.ai changes things without notice — advertised prices, model availability, even API shapes. .github/workflows/drift-watch.yml runs scripts/drift-watch.mjs weekly (and on demand) to scan for it: paused/removed slugs, pricing that no longer matches the PRICING table, and new models in kie's catalog. Findings land in a single rolling GitHub issue. Add a KIE_API_KEY repo secret to enable the per-slug liveness probes (0 credits — empty-input validation errors); the pricing and new-model scans need no secret. Run locally with node scripts/drift-watch.mjs.

Releasing

Releases are automated by .github/workflows/release.yml. To cut a release:

1. Bump the version in package.json, server.json (both the top-level version and packages[0].version), and server.mjs (SERVER_INFO + the /health handler), and add a ## [X.Y.Z] section to CHANGELOG.md. Merge to main.
2. Tag and push:

   git tag vX.Y.Z && git push origin vX.Y.Z

The workflow verifies the tag matches every in-repo version string, publishes to npm with provenance (NPM_TOKEN repo secret), and creates the GitHub Release using the matching CHANGELOG section as the notes. A tag whose version doesn't match the code fails fast without publishing. workflow_dispatch is an emergency manual publish of the current package.json version.

Credits

• Built with the MCP TypeScript SDK
• Powered by kie.ai — affordable unified API for 100+ AI models
• Model intelligence by Averiguare — "No sabes hasta que averiguas — y averiguo en todas partes."

License

MIT