L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Design et création · SKILL.md

inkscape-mcp-connector

inkscape-mcp-connector

MCP connector for Inkscape vector graphics – enables AI-powered SVG creation, path manipulation, and design automation through Claude

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: inkscape-mcp-connector description: "MCP connector for Inkscape vector graphics – enables AI-powered SVG creation, path manipulation, and design automation through Claude" license: GPL tags: ["creative","vector-graphics","mcp","inkscape","svg"] difficulty: advanced time_to_master: "4-8 weeks" version: "1.0.0"

Inkscape MCP Connector

Overview

This skill enables Claude to interact with Inkscape through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Inkscape's CLI/D-Bus, allowing natural language control of Inkscape operations, intelligent automation, and AI-powered assistance for Inkscape workflows.

When to Use This Skill

  • SVG generation from natural language descriptions
  • Path operations and boolean operations
  • Text-to-path conversion and typography
  • Batch SVG processing and optimization
  • Extension and filter development

Architecture

┌─────────────┐     ┌─────────────────┐     ┌──────────────────┐
│   Claude     │────▶│   MCP Server    │────▶│   Inkscape         │
│   (Client)   │◀────│   (Python/TypeScript)  │◀────│   (CLI/D-Bus     )│
└─────────────┘     └─────────────────┘     └──────────────────┘

Core Concepts

MCP Server Setup

The connector implements an MCP server that exposes Inkscape operations as tools Claude can invoke. The server translates natural language intentions into CLI/D-Bus calls.

Key Endpoints/Interfaces

inkscape --actions, inkscape --export-*, inkscape --verb, org.inkscape.Inkscape

Implementation

// Inkscape MCP Server Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

const server = new McpServer({
  name: "inkscape-mcp-connector",
  version: "1.0.0",
});

// Tool: List/Query Resources
server.tool(
  "list_resources",
  "List and query Inkscape resources with optional filters",
  {
    query: z.string().optional().describe("Search query or filter"),
    limit: z.number().optional().describe("Max results to return"),
  },
  async ({ query, limit }) => {
    // Call Inkscape CLI/D-Bus
    const response = await fetch(`${BASE_URL}inkscape --actions`, {
      headers: { "Authorization": `Bearer ${API_KEY}` },
    });
    const data = await response.json();
    return {
      content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
    };
  }
);

// Tool: Create Resource
server.tool(
  "create_resource",
  "Create a new resource in Inkscape",
  {
    name: z.string().describe("Resource name"),
    config: z.object({}).passthrough().optional().describe("Resource configuration"),
  },
  async ({ name, config }) => {
    const response = await fetch(`${BASE_URL}inkscape --actions`, {
      method: "POST",
      headers: {
        "Authorization": `Bearer ${API_KEY}`,
        "Content-Type": "application/json",
      },
      body: JSON.stringify({ name, ...config }),
    });
    const data = await response.json();
    return {
      content: [{ type: "text", text: `Created: ${JSON.stringify(data)}` }],
    };
  }
);

// Tool: Analyze/Report
server.tool(
  "analyze",
  "AI-powered analysis of Inkscape data",
  {
    type: z.string().describe("Analysis type"),
    timeframe: z.string().optional().describe("Time range for analysis"),
  },
  async ({ type, timeframe }) => {
    // Fetch data and provide AI analysis
    const response = await fetch(`${BASE_URL}inkscape --actions`, {
      headers: { "Authorization": `Bearer ${API_KEY}` },
    });
    const data = await response.json();
    return {
      content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
    };
  }
);

// Start server
const transport = new StdioServerTransport();
await server.connect(transport);

Claude Desktop Configuration

{
  "mcpServers": {
    "inkscape-mcp-connector": {
      "command": "node",
      "args": ["path/to/inkscape-mcp-connector/index.js"],
      "env": {
        "INKSCAPE_API_KEY": "your-api-key",
        "INKSCAPE_BASE_URL": "https://your-instance-url"
      }
    }
  }
}

Best Practices

  1. Authentication: Store API keys securely using environment variables; never hardcode credentials
  2. Rate Limiting: Implement request throttling to respect Inkscape API rate limits
  3. Error Handling: Provide clear, actionable error messages for common failure scenarios
  4. Pagination: Handle paginated responses for large datasets efficiently
  5. Caching: Cache frequently accessed read-only data to reduce API calls
  6. Security: Validate all inputs before passing to the Inkscape API; sanitize outputs
  7. Logging: Log all API interactions for debugging and audit purposes

Example Prompts

"Create an SVG logo with a circular badge containing a star and company name in a modern font"

Security Considerations

  • All API credentials must be stored as environment variables
  • Implement input validation and sanitization for all tool parameters
  • Use HTTPS for all API communications
  • Follow the principle of least privilege for API token permissions
  • Audit log all write operations for compliance tracking

Resources

Changelog

VersionDateChanges
1.0.02026-04-01Initial MCP connector skill

Part of SkillGalaxy - 10,000+ comprehensive skills for AI-assisted development.

Skills enregistrées