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AceDataCloud

FluxMCP

by AceDataCloud
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Hybrid

flux_generate_image

Turn text prompts into AI-generated images with Flux. Specify a descriptive prompt and desired size to produce artwork or photos for your project.

Instructions

Generate AI images from a text prompt using Flux.

Flux is a family of fast, high-quality image generation models by Black Forest Labs.
Different models offer different tradeoffs between speed, quality, and capabilities.

Use this when:
- You want to create new images from a text description
- You need high-quality AI-generated artwork or photos
- You want fast image generation with good prompt following

For editing existing images, use flux_edit_image instead.

Returns:
    Task ID and generated image information including URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeYesRequired image size. For flux-dev: pixel dimensions like '1024x1024' (256-1440px, multiples of 32). For flux-2-flex/pro/max: pixel dimensions (x >= 64, multiples of 32). For kontext models: image ratios like '1:1', '16:9', '9:16', '4:3', '3:2', '2:3', '4:5', '5:4', '3:4', '21:9', '9:21'.
countNoNumber of images to generate. Only supported for generate action. Default is 1.
modelNoFlux model to use for generation. Options: - flux-dev: Fast development model, good balance of speed and quality (default) - flux-pro: Higher quality production model - flux-2-flex: Flux 2 flexible model, pixel sizes (x >= 64, multiple of 32) - flux-2-pro: Flux 2 professional model, high quality - flux-2-max: Flux 2 maximum-quality model - flux-2-klein: Flux 2 klein model, efficient generation - flux-kontext-pro: Context-aware model for editing and style transfer - flux-kontext-max: Maximum context model for complex editing tasksflux-dev
promptYesDescription of the image to generate. Be descriptive about style, subject, lighting, and composition. Examples: 'A majestic mountain landscape at golden hour, photorealistic', 'Cyberpunk street scene with neon lights and rain, cinematic', 'Minimalist logo design of a phoenix, vector art style'
callback_urlNoWebhook callback URL for asynchronous notifications. When provided, the API will POST to this URL when the image is generated.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed5 schema fields changedv0.1.9
    • removedInput schema / properties / size / anyOf
      Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
    • removedInput schema / properties / size / default
      Removed value: -null
    • changedInput schema / properties / size / description
      Previous value: -"Image size. For flux-dev: pixel dimensions like '1024x1024' (256-1440px, multiples of 32). For flux-2-flex/pro/max: pixel dimensions (x >= 64, multiples of 32). For kontext models: image ratios like '1:1', '16:9', '9:16', '4:3', '3:2', '2:3', '4:5', '5:4', '3:4', '21:9', '9:21'. Default varies by model."New value: +"Required image size. For flux-dev: pixel dimensions like '1024x1024' (256-1440px, multiples of 32). For flux-2-flex/pro/max: pixel dimensions (x >= 64, multiples of 32). For kontext models: image ratios like '1:1', '16:9', '9:16', '4:3', '3:2', '2:3', '4:5', '5:4', '3:4', '21:9', '9:21'."
    • addedInput schema / properties / size / type
      Added value: +"string"
    • changedInput schema / required
      Previous value: -[
-  "prompt"
-]New value: +[
+  "prompt",
+  "size"
+]
  2. Changed2 schema fields changedv0.1.7
    • changedInput schema / properties / model / description
      Previous value: -"Flux model to use for generation. Options:\n- flux-dev: Fast development model, good balance of speed and quality (default)\n- flux-pro: Higher quality production model\n- flux-2-flex: Flux 2 flexible model, pixel sizes (x >= 64, multiple of 32)\n- flux-2-pro: Flux 2 professional model, high quality\n- flux-2-max: Flux 2 maximum-quality model\n- flux-kontext-pro: Context-aware model for editing and style transfer\n- flux-kontext-max: Maximum context model for complex editing tasks"New value: +"Flux model to use for generation. Options:\n- flux-dev: Fast development model, good balance of speed and quality (default)\n- flux-pro: Higher quality production model\n- flux-2-flex: Flux 2 flexible model, pixel sizes (x >= 64, multiple of 32)\n- flux-2-pro: Flux 2 professional model, high quality\n- flux-2-max: Flux 2 maximum-quality model\n- flux-2-klein: Flux 2 klein model, efficient generation\n- flux-kontext-pro: Context-aware model for editing and style transfer\n- flux-kontext-max: Maximum context model for complex editing tasks"
    • changedInput schema / properties / model / enum
      Previous value: -[
-  "flux-dev",
-  "flux-pro",
-  "flux-kontext-pro",
-  "flux-kontext-max",
-  "flux-2-flex",
-  "flux-2-pro",
-  "flux-2-max"
-]New value: +[
+  "flux-dev",
+  "flux-pro",
+  "flux-kontext-pro",
+  "flux-kontext-max",
+  "flux-2-flex",
+  "flux-2-pro",
+  "flux-2-max",
+  "flux-2-klein"
+]
  3. Changed2 schema fields changedv0.1.6
    • changedInput schema / properties / model / description
      Previous value: -"Flux model to use for generation. Options:\n- flux-dev: Fast development model, good balance of speed and quality (default)\n- flux-pro: Higher quality production model\n- flux-pro-1.1: Improved production model with better prompt following\n- flux-pro-1.1-ultra: Highest quality, supports aspect ratios instead of pixel sizes\n- flux-kontext-pro: Context-aware model for editing and style transfer\n- flux-kontext-max: Maximum context model for complex editing tasks"New value: +"Flux model to use for generation. Options:\n- flux-dev: Fast development model, good balance of speed and quality (default)\n- flux-pro: Higher quality production model\n- flux-2-flex: Flux 2 flexible model, pixel sizes (x >= 64, multiple of 32)\n- flux-2-pro: Flux 2 professional model, high quality\n- flux-2-max: Flux 2 maximum-quality model\n- flux-kontext-pro: Context-aware model for editing and style transfer\n- flux-kontext-max: Maximum context model for complex editing tasks"
    • changedInput schema / properties / size / description
      Previous value: -"Image size. For flux-dev/pro/pro-1.1: pixel dimensions like '1024x1024' (256-1440px, multiples of 32). For flux-pro-1.1-ultra and kontext models: aspect ratios like '1:1', '16:9', '9:16', '4:3', '3:2', '2:3', '4:5', '5:4', '3:4', '21:9', '9:21'. Default varies by model."New value: +"Image size. For flux-dev: pixel dimensions like '1024x1024' (256-1440px, multiples of 32). For flux-2-flex/pro/max: pixel dimensions (x >= 64, multiples of 32). For kontext models: image ratios like '1:1', '16:9', '9:16', '4:3', '3:2', '2:3', '4:5', '5:4', '3:4', '21:9', '9:21'. Default varies by model."
  4. Addedv0.1.3
  5. Removedv0.1.2
  6. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full transparency burden. It mentions returning a 'Task ID and generated image information including URLs,' which hints at async/task-based behavior. However, it does not explain whether generation is synchronous, how long it may take, whether it should be polled via flux_get_task, or side effects such as cost/rate limits. Some insight is given, but it is not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The structure is effective: a one-sentence purpose, brief context, use-case bullets, a sibling-tool contrast, and a returns section. It is slightly wordier than necessary—some model-family background could be trimmed—but every section earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter image-generation tool, the description provides enough high-level context: generation purpose, model family tradeoff, use cases, editing alternative, and output type. It does not explicitly mention how to monitor task progress or poll until successful generation, but the 'Task ID' return value and the presence of flux_get_task make a workable inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description refers to prompts and mentions high-quality generation, but does not add substantial meaning beyond the schema's parameter descriptions. The schema already documents model recommendations, size formats, count/defaults, and callback_url semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Generate AI images from a text prompt using Flux.' It clearly distinguishes this tool from flux_edit_image by explicitly stating that editing existing images should use the sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'Use this when' section lists three concrete scenarios for new image generation, and explicitly states that editing existing images should use flux_edit_image instead. This provides clear when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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