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Design und Kreativität · SKILL.md

grav-cms-mcp-connector

grav-cms-mcp-connector

MCP connector for Grav flat-file CMS – enables AI-powered content creation, theme management, and Markdown-based site management through Claude

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: grav-cms-mcp-connector description: "MCP connector for Grav flat-file CMS – enables AI-powered content creation, theme management, and Markdown-based site management through Claude" license: MIT tags: ["dev","cms","mcp","grav","markdown"] difficulty: intermediate time_to_master: "4-8 weeks" version: "1.0.0"

Grav Cms MCP Connector

Overview

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

When to Use This Skill

  • Page creation and frontmatter configuration
  • Theme and blueprint customization
  • Plugin configuration and management
  • Twig template generation with AI
  • Multi-language content management

Architecture

┌─────────────┐     ┌─────────────────┐     ┌──────────────────┐
│   Claude     │────▶│   MCP Server    │────▶│   Grav Cms         │
│   (Client)   │◀────│   (TypeScript)  │◀────│   (CLI/File-based)│
└─────────────┘     └─────────────────┘     └──────────────────┘

Core Concepts

MCP Server Setup

The connector implements an MCP server that exposes Grav Cms operations as tools Claude can invoke. The server translates natural language intentions into CLI/File-based calls.

Key Endpoints/Interfaces

grav pages, grav backup, grav install, grav cache, grav composer

Implementation

// Grav Cms 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: "grav-cms-mcp-connector",
  version: "1.0.0",
});

// Tool: List/Query Resources
server.tool(
  "list_resources",
  "List and query Grav Cms 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 Grav Cms CLI/File-based
    const response = await fetch(`${BASE_URL}grav pages`, {
      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 Grav Cms",
  {
    name: z.string().describe("Resource name"),
    config: z.object({}).passthrough().optional().describe("Resource configuration"),
  },
  async ({ name, config }) => {
    const response = await fetch(`${BASE_URL}grav pages`, {
      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 Grav Cms 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}grav pages`, {
      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": {
    "grav-cms-mcp-connector": {
      "command": "node",
      "args": ["path/to/grav-cms-mcp-connector/index.js"],
      "env": {
        "GRAV_CMS_API_KEY": "your-api-key",
        "GRAV_CMS_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 Grav Cms 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 Grav Cms API; sanitize outputs
  7. Logging: Log all API interactions for debugging and audit purposes

Example Prompts

"Create a documentation site structure with sidebar navigation and search functionality"

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

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