mcp-tokenflux-images

Generate images using AI models via TokenFlux API. Use when creating AI-generated images, artwork, or visual content. Triggers on "generate image", "create picture", "AI art", "image generation", "TokenFlux".

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "mcp-tokenflux-images" with this command: npx skills add vaayne/cc-plugins/vaayne-cc-plugins-mcp-tokenflux-images

TokenFlux Image Generation

MCP service at https://tokenflux.ai/v1/images/mcp (http) with 4 tools.

Requirements

  • mh CLI must be installed. If not available, install with:
    curl -fsSL https://raw.githubusercontent.com/vaayne/mcphub/main/scripts/install.sh | sh
    
  • TOKENFLUX_API_KEY environment variable must be set with your TokenFlux API key

Usage

List tools: mh list -u https://tokenflux.ai/v1/images/mcp --header "x-api-key:${TOKENFLUX_API_KEY}"

Get tool details: mh inspect -u https://tokenflux.ai/v1/images/mcp --header "x-api-key:${TOKENFLUX_API_KEY}" <tool-name>

Invoke tool: mh invoke -u https://tokenflux.ai/v1/images/mcp --header "x-api-key:${TOKENFLUX_API_KEY}" <tool-name> '{"param": "value"}'

Workflow

  1. List models first: Use listModels to discover available image generation models
  2. Get model schema: Use getModel with the chosen model_id to get the required input_schema
  3. Generate image: Use generateImage with the correct input format from the schema
  4. Poll if needed: If generation returns status: 'processing', use getGeneration to poll until complete

Notes

  • Run inspect before invoking unfamiliar tools to get full parameter schema
  • Timeout: 30s default, use --timeout <seconds> to adjust
  • generateImage waits up to 30 seconds; if still processing, poll with getGeneration
  • Always call getModel before generateImage to understand the correct input format

Tools

  • listModels: List all available VLM models with their IDs, names, descriptions, and pricing. Use this first to discover valid model_id values for generate_image. This tool takes no parameters.
  • getModel: Get detailed information about a specific VLM model including its input_schema. The input_schema is a JSON Schema describing the required input object for generate_image. Always call this before generate_image to understand the correct input format.
  • generateImage: Generate an image using a VLM model. IMPORTANT: Call get_model first to get the input_schema for your model. This tool waits up to 30 seconds for completion. If the image is ready, returns {id, status: 'succeeded', images: [...]}. If still processing after 30s, returns {id, status: 'processing'} - use get_generation to poll.
  • getGeneration: Get the status and result of an image generation request. Use the id returned by generate_image to poll until status is 'succeeded' or 'failed'. Returns {id, model, status, images?, error?, cost?}.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

mcp-jetbrains-ide

No summary provided by upstream source.

Repository SourceNeeds Review
General

mcp-exa-search

No summary provided by upstream source.

Repository SourceNeeds Review
General

mcp-context7-docs

No summary provided by upstream source.

Repository SourceNeeds Review
General

web-fetch

No summary provided by upstream source.

Repository SourceNeeds Review