Skip to main content
Glama
frankdeno

FLUX Image Generator MCP Server

by frankdeno

quickImage

Generate images from text prompts using the FLUX model with default settings. Provide a description to create and save visual content.

Instructions

Quickly generate an image based on a text prompt with default settings

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText description of the image to generate
customPathNoCustom path to save the generated image

Implementation Reference

  • The handler logic for the 'quickImage' tool within the CallToolRequestSchema handler. It validates the prompt argument, calls the shared generateImage function with default parameters and a custom filename, then constructs a text response with the image URL and local save path.
    case "quickImage": {
      // Validate parameters
      if (typeof args.prompt !== 'string') {
        throw new Error("Invalid prompt: must be a string");
      }
    
      // Simple version with just a prompt
      const result = await generateImage(args.prompt, {
        saveImage: true,
        filename: `flux_quick_${Date.now()}.png`,
        customPath: typeof args.customPath === 'string' ? args.customPath : undefined
      });
      
      // Return a plain text response with the image URL and save location
      let textContent = `Image generated\nLink: ${result.image_url}`;
      
      // Add information about where the image was saved
      if (result.local_path) {
        textContent += `\nImage saved to: ${result.local_path}`;
      }
      
      return {
        content: [
          { type: "text", text: textContent }
        ],
        isError: false,
      };
    }
  • The Tool schema definition for 'quickImage', specifying name, description, and input schema requiring a 'prompt' string and optional 'customPath'.
    export const QUICK_IMAGE_TOOL: Tool = {
      name: "quickImage",
      description: "Quickly generate an image based on a text prompt with default settings",
      inputSchema: {
        type: "object",
        properties: {
          prompt: {
            type: "string",
            description: "Text description of the image to generate"
          },
          customPath: {
            type: "string",
            description: "Custom path to save the generated image"
          }
        },
        required: ["prompt"]
      }
    };
  • src/index.ts:48-54 (registration)
    Registration of the 'quickImage' tool (as QUICK_IMAGE_TOOL) in the listTools request handler, making it available to clients.
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [
        GENERATE_IMAGE_TOOL,
        QUICK_IMAGE_TOOL,
        BATCH_GENERATE_IMAGES_TOOL
      ],
    }));
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'quickly' and 'default settings,' hinting at speed and simplicity, but lacks details on permissions, rate limits, output format (e.g., image type, size), or whether it's a read-only or mutating operation. This is inadequate for a tool with no annotation coverage.

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

Conciseness5/5

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and appropriately sized for the tool's complexity.

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

Completeness2/5

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

Given no annotations, no output schema, and a mutation-like tool (image generation), the description is incomplete. It lacks details on behavioral traits, output handling, and differentiation from siblings. While concise, it doesn't provide enough context for effective agent use.

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 schema already documents both parameters ('prompt' and 'customPath'). The description adds no additional meaning beyond implying 'default settings' might affect generation, but it doesn't clarify parameter interactions or usage. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'generate an image based on a text prompt with default settings.' It specifies the verb ('generate') and resource ('image'), though it doesn't explicitly differentiate from sibling tools like 'generateImage' or 'batchGenerateImages' beyond mentioning 'default settings.'

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus its siblings. It mentions 'default settings,' which might imply a simpler or faster alternative, but it doesn't specify contexts, exclusions, or named alternatives like 'batchGenerateImages' for batch processing or 'generateImage' for more control.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/frankdeno/flux-image-generator-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server