Skip to main content
Glama
deepakkumardewani

Color Scheme Generator MCP Server

generate_monochrome_scheme

Generate a monochrome color scheme with variations of a single hue for design projects. Input a seed color and specify the number of colors to create.

Instructions

Generates a monochrome color scheme with variations of a single hue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
colorYesThe seed color in hex (098765), RGB (0,71,171), or HSL (215,100%,34%) format
countNoNumber of colors to generate (3-10, default: 5)

Implementation Reference

  • The handler function for the generate_monochrome_scheme tool. It extracts 'color' and 'count' from input args, generates the monochrome scheme using the shared helper, and returns a JSON-formatted text response.
    async (args) => {
      const { color, count } = args;
      const result = await generateColorScheme(color, "monochrome", count);
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(result, null, 2),
          },
        ],
      };
    }
  • Shared input schema definition using Zod for validating the tool's parameters: 'color' (string) and optional 'count' (number, 3-10). Used by generate_monochrome_scheme and other scheme tools.
    const colorSchemeInputShape = {
      color: z
        .string()
        .describe(
          "The seed color in hex (098765), RGB (0,71,171), or HSL (215,100%,34%) format"
        ),
      count: z
        .number()
        .int()
        .min(3)
        .max(10)
        .default(5)
        .optional()
        .describe("Number of colors to generate (3-10, default: 5)"),
    };
  • Registration function registerMonochromeScheme that calls server.tool to register the tool with name, description, schema, and handler. Invoked from registerTools().
    function registerMonochromeScheme() {
      server.tool(
        "generate_monochrome_scheme",
        "Generates a monochrome color scheme with variations of a single hue",
        colorSchemeInputShape,
        async (args) => {
          const { color, count } = args;
          const result = await generateColorScheme(color, "monochrome", count);
          return {
            content: [
              {
                type: "text",
                text: JSON.stringify(result, null, 2),
              },
            ],
          };
        }
      );
    }
  • Shared helper function that handles the core logic: parses color, constructs API URL for the specified mode ('monochrome'), fetches from The Color API, formats colors (hex, rgb, hsl, name), and returns structured scheme data.
    async function generateColorScheme(
      color: string,
      mode: string,
      count: number = 5
    ) {
      const { param, value } = parseColorInput(color);
      const url = `https://www.thecolorapi.com/scheme?${param}=${value}&mode=${mode}&count=${count}&format=json`;
    
      try {
        const response = await fetch(url);
        if (!response.ok) {
          throw new Error(
            `Color API request failed: ${response.status} ${response.statusText}`
          );
        }
    
        const data: any = await response.json();
    
        if (!data.colors || !Array.isArray(data.colors)) {
          throw new Error("Invalid response from Color API");
        }
    
        // Format the response for better readability
        const colors = data.colors.map((color: any, index: number) => ({
          position: index + 1,
          hex: color.hex?.value || "N/A",
          rgb: color.rgb
            ? `rgb(${color.rgb.r}, ${color.rgb.g}, ${color.rgb.b})`
            : "N/A",
          hsl: color.hsl
            ? `hsl(${color.hsl.h}, ${color.hsl.s}%, ${color.hsl.l}%)`
            : "N/A",
          name: color.name?.value || "Unknown",
        }));
    
        return {
          scheme_mode: mode,
          seed_color: data.seed?.hex?.value || value,
          color_count: colors.length,
          colors: colors,
        };
      } catch (error) {
        console.error(`Error generating ${mode} color scheme:`, error);
        throw error;
      }
    }
  • Helper function that parses and normalizes color input strings (hex with/without #, RGB, HSL) into standardized {param, value} for the Color API.
    function parseColorInput(color: string): { param: string; value: string } {
      const cleanColor = color.trim();
    
      // Check for hex format
      if (cleanColor.startsWith("#")) {
        return { param: "hex", value: cleanColor.substring(1) };
      } else if (/^[0-9A-Fa-f]{6}$/.test(cleanColor)) {
        return { param: "hex", value: cleanColor };
      }
    
      // Check for RGB format
      if (
        cleanColor.toLowerCase().includes("rgb") ||
        /^\d+,\d+,\d+$/.test(cleanColor)
      ) {
        const rgbMatch = cleanColor.match(/(\d+),\s*(\d+),\s*(\d+)/);
        if (rgbMatch) {
          return {
            param: "rgb",
            value: `${rgbMatch[1]},${rgbMatch[2]},${rgbMatch[3]}`,
          };
        }
      }
    
      // Check for HSL format
      if (cleanColor.toLowerCase().includes("hsl") || cleanColor.includes("%")) {
        const hslMatch = cleanColor.match(/(\d+),\s*(\d+)%,\s*(\d+)%/);
        if (hslMatch) {
          return {
            param: "hsl",
            value: `${hslMatch[1]},${hslMatch[2]}%,${hslMatch[3]}%`,
          };
        }
      }
    
      // Default to hex if format is unclear
      return { param: "hex", value: cleanColor.replace("#", "") };
    }
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 of behavioral disclosure. It states the tool generates a color scheme but does not explain what the output looks like (e.g., list of colors, format), whether it's deterministic, or if there are any side effects (e.g., caching). For a generation tool with no annotation coverage, this lack of detail is a significant gap.

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 that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and constraint, making it easy to understand at a glance. Every part of the sentence earns its place by conveying essential information.

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

Completeness3/5

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

Given the tool's moderate complexity (generation with two parameters) and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on output format, behavioral traits, and usage context. With no annotations and incomplete behavioral transparency, it falls short of being fully helpful for an AI agent.

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 fully documents both parameters ('color' and 'count'). The description does not add any meaning beyond what the schema provides, such as explaining how the seed color influences variations or the aesthetic impact of the count. Baseline 3 is appropriate when 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: 'Generates a monochrome color scheme with variations of a single hue.' It specifies the verb ('generates'), resource ('monochrome color scheme'), and key constraint ('variations of a single hue'). However, it does not explicitly differentiate from sibling tools like 'generate_monochrome_dark_scheme' or 'generate_monochrome_light_scheme', which likely produce similar monochrome schemes with specific brightness variations.

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 alternatives. It does not mention sibling tools or contexts where a monochrome scheme is preferred over other types (e.g., complement or triad schemes). Without such guidance, users must infer usage based on the tool name alone, which is insufficient for optimal selection.

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/deepakkumardewani/color-scheme-mcp'

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