higgsfield-mcp
MCP server for Higgsfield AI that enables image and video generation using 16+ models through Claude, Cursor, or any MCP-compatible client.
README
Higgsfield MCP
MCP server for Higgsfield AI — generate images and videos with 16+ models through Claude, Cursor, or any MCP-compatible client.
Models
Image
| Model | ID | Key Features |
|---|---|---|
| Nano Banana 2 | nano-banana-2 |
Fast, reference images (up to 16), 1k/2k/4k |
| Nano Banana 1 | nano-banana-1 |
Reference images, multi-ref |
| Soul v2 | soul-v2 |
Stylized, 720p/1080p/2k |
| OpenAI Hazel | openai-hazel |
GPT-Image-1.5, low/medium/high/4k |
Video
| Model | ID | Key Features |
|---|---|---|
| Kling 3.0 | kling3 |
Best quality, start/end frames, sound, 720p/1080p, std/pro |
| Kling 3.0 Omni FLF | kling-o3-flf |
First/last frame control |
| Kling 2.6 | kling2-6 |
Balanced quality/cost |
| Kling 2.5 Turbo | kling2-5-turbo |
Unlimited plan credits |
| Kling 2.1 | kling |
Budget option |
| Grok Video | grok |
xAI video model |
| Wan 2.6 | wan2-6 |
Open-source model |
| Wan 2.5 | wan2-5-video |
16:9 or 9:16 only |
| Seedance 1.5 | seedance1-5 |
ByteDance latest |
| Seedance Pro | seedance |
ByteDance pro |
| Veo 3 | veo3 |
Google DeepMind |
| Sora 2 | sora2-video |
OpenAI, 4/8/12s durations |
| Image2Video | image2video |
Requires input image |
Tools
| Tool | Description |
|---|---|
higgsfield_generate_image |
Generate images (returns job_id) |
higgsfield_generate_video |
Generate videos (returns job_id) |
higgsfield_wait_for_job |
Poll job(s) until complete, return result URLs |
higgsfield_get_job |
Check single job status (no polling) |
higgsfield_list_jobs |
List recent jobs with status and URLs |
higgsfield_cancel_job |
Cancel a running job |
higgsfield_check_cost |
Dry-run cost estimate for image generation |
higgsfield_get_credits |
Account balance and plan info |
higgsfield_list_models |
List all models with supported parameters |
higgsfield_video_pricing |
Static pricing reference |
higgsfield_browser_status |
Check Helm daemon connection |
higgsfield_refresh_token |
Manually set JWT token |
higgsfield_refresh_credentials |
Update Clerk session cookies for auto-refresh |
Prerequisites
- Bun runtime
- A Higgsfield AI account (with credits)
- Helm daemon running with Chrome extension — used to get auth tokens from your browser session
- (Optional) curl-impersonate — improves reliability for GET requests. Set
CURL_IMPERSONATE_BINenv var if the binary isn't in PATH. Falls back to nativefetchif not installed.
Setup
# Clone
git clone https://github.com/jfikrat/higgsfield-mcp.git
cd higgsfield-mcp
# Install dependencies
bun install
# Run the server
bun run src/index.ts
Claude Code / Claude Desktop
Add to your MCP config (~/.claude/claude_desktop_config.json or MCP settings):
{
"mcpServers": {
"higgsfield": {
"command": "bun",
"args": ["run", "/path/to/higgsfield-mcp/src/index.ts"]
}
}
}
Authentication
The server authenticates via Clerk session tokens from your Higgsfield browser session. There are three methods (tried in order):
- Auto-refresh — Clerk API refresh using saved session cookies (preferred)
- Helm browser bridge — Extracts token from your logged-in Chrome session via Helm daemon
- Manual — Paste a JWT token via
higgsfield_refresh_token
First-time setup:
- Log in to higgsfield.ai in Chrome
- Make sure the Helm daemon is running (
systemctl --user start helm-daemon) - Use
higgsfield_browser_statusto verify the connection - The server will auto-extract tokens from your browser session
If auto-refresh stops working (tokens expire ~every 7 days):
- Open Chrome DevTools on higgsfield.ai
- Copy cookies from the
clerk.higgsfield.aidomain - Run
higgsfield_refresh_credentialswith the cookie string
Settings are stored at ~/.config/higgsfield-mcp/settings.json (permissions: 600).
Architecture
src/
├── index.ts # MCP server entry point
├── models.ts # Model metadata, validation, param builders
├── api.ts # HTTP client (GET/POST/DELETE)
├── auth.ts # Token management (Clerk refresh + browser fallback)
├── browser-post.ts # Helm daemon bridge for browser-based POST
├── curl-fetch.ts # curl-impersonate wrapper with native fallback
├── config.ts # Secure settings storage (~/.config/higgsfield-mcp/)
├── tracker.ts # Generation gallery tracker
└── tools/
├── account.ts # Account, credits, model listing tools
├── image.ts # Image generation tools
└── video.ts # Video generation + job polling tools
How It Works
Higgsfield uses DataDome bot protection that blocks non-browser POST requests. This server handles it with a two-layer approach:
- GET/DELETE requests go through
curl-impersonate(or nativefetchas fallback) with browser-like TLS fingerprints - POST requests are routed through the Helm daemon, which executes
fetch()inside your actual Chrome tab on higgsfield.ai — DataDome sees a real browser
License
MIT
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