mcp-generic-prompts by arvato-systems-romania - MCP Server

MCP Generic Prompt Server

A comprehensive Model Context Protocol (MCP) server that provides a curated library of professional developer AI prompts organized by technology and use case.

🎯 Overview

This MCP server provides:

Professional Prompts across multiple categories and technologies
Hierarchical Organization by framework (React, Angular, Vue, Python, Java, Node.js)
Mustache Templating for flexible variable substitution
Search Capabilities to discover relevant prompts
MCP Resource Access for programmatic prompt retrieval

📦 Installation

npm install
npm run build

The built server will be available at .

🚀 Quick Start

Claude Desktop

Add to your Claude Desktop config:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "generic-prompts": {
      "command": "node",
      "args": ["/absolute/path/to/mcp-generic-prompt/dist/mcp-entry.cjs"]
    }
  }
}

Restart Claude Desktop and look for the 🔌 icon to confirm the server is connected.

Other Tools

This server works with many MCP-compatible tools:

Roo Code - Advanced AI coding assistant for VSCode
Cline - VSCode extension (formerly Claude Dev)
Continue.dev - Open-source AI code assistant for VSCode/JetBrains
GitHub Copilot Chat - GitHub's AI pair programmer (preview support)
Custom clients - Python, TypeScript, Node.js applications
Web apps - FastAPI, Express.js backends with React/Vue frontends
CLI tools - Bash scripts, Python CLIs

📖 See for detailed setup instructions and for ready-to-use configuration files.

Basic Usage Example

// Render a prompt with variables
await client.callTool({
  name: "renderPrompt",
  arguments: {
    id: "react-hooks-optimization",
    variables: {
      component_name: "UserDashboard",
      react_code: "const [data, setData] = useState(null)...",
      framework_version: "18.2.0"
    }
  }
});

📚 Prompt Library

Featured Prompts

React Hooks Optimization

{
  id: "react-hooks-optimization",
  category: "frontend-react",
  // Analyzes React hooks for performance issues, missing dependencies,
  // unnecessary re-renders, and optimization opportunities
}

FastAPI Best Practices

{
  id: "fastapi-best-practices",
  category: "backend-python",
  // Reviews FastAPI architecture for dependency injection,
  // middleware design, and production-ready patterns
}

SQL Query Optimization

{
  id: "sql-query-optimization",
  category: "database",
  // Analyzes SQL queries for performance issues, indexing strategies,
  // and query plan optimization (PostgreSQL, MySQL)
}

See for the complete catalog.

🛠️ Available Tools

renderPrompt

Renders a prompt template with variable substitution.

Parameters:

id (string, required): Prompt identifier
variables (object, optional): Key-value pairs for variable substitution

Example:

{
  "id": "spring-boot-performance-optimization",
  "variables": {
    "project_name": "OrderService",
    "spring_code": "...",
    "spring_version": "3.2.0",
    "java_version": "17",
    "performance_issue": "Slow API responses"
  }
}

searchPrompts

Search prompts by name, description, or tags.

Parameters:

query (string, required): Search query

Example:

{
  "query": "security"
}

Returns matching prompts with their IDs, titles, and descriptions.

📂 Project Structure

mcp-generic-prompt/
├── prompts/                      # Hierarchical prompt library
│   ├── PROMPT_INDEX.md          # Complete prompt catalog
│   ├── general/                 # Cross-cutting prompts (19)
│   │   ├── code_review.json
│   │   ├── testing.json         # Flaky tests, coverage (2)
│   │   ├── performance.json     # Profiling, memory leaks (2)
│   │   ├── refactoring.json     # Architecture, style (4)
│   │   └── ...
│   ├── frontend/                # Frontend prompts (10)
│   │   ├── react/
│   │   ├── angular/
│   │   └── vue/
│   ├── backend/                 # Backend prompts (13)
│   │   ├── python/
│   │   ├── nodejs/
│   │   └── java/
│   ├── database/                # Database optimization (1)
│   ├── devops/                  # DevOps & CI/CD (7)
│   ├── security/                # Security auditing (7)
│   └── ai-ml/                   # AI/ML integrations (5)
├── src/
│   ├── mcp/
│   │   └── server.ts            # MCP server implementation
│   ├── utils/
│   │   └── loadPrompts.ts       # Recursive prompt loader
│   └── mcp-entry.ts             # Entry point
├── docs/
│   ├── API.md                   # API documentation
│   └── PROMPTS.md               # Prompt creation guide
└── dist/                        # Compiled output

🔍 Prompt Format

Each prompt follows a comprehensive JSON schema:

{
  "id": "kebab-case-id",
  "title": "Human Readable Title",
  "description": "1-2 sentence description",
  "category": "technology-category",
  "tags": ["tag1", "tag2"],
  "template": "Detailed prompt with {{placeholders}}",
  "input_schema": {
    "type": "object",
    "properties": {
      "param_name": {
        "type": "string",
        "description": "Parameter description"
      }
    },
    "required": ["param_name"]
  },
  "examples": [{
    "input": { "param_name": "value" },
    "output_outline": "Expected output description"
  }],
  "version": "1.0.0",
  "created_utc": "2025-01-15T10:00:00Z",
  "last_modified_utc": "2025-01-15T10:00:00Z"
}

📖 Documentation

: Setup with Claude Desktop, Cline, Continue.dev, and custom clients
: Complete catalog of all prompts
: Server API and module reference
: How to create and use prompts

🎨 Key Features

Hierarchical Organization

Prompts are organized by technology and framework:

Framework-specific prompts (React hooks, Vue composables, Angular RxJS)
Technology-specific optimizations (Java build tools, Python async patterns)
Domain-specific audits (security, performance, testing)

Comprehensive Prompts

Each prompt includes:

Detailed templates with multiple analysis sections
JSON Schema for input validation
Realistic examples with expected outputs
Version tracking and authorship

Smart Search

Search across:

Prompt titles and descriptions
Category and tag metadata
Technology-specific keywords

🤝 Contributing

Adding New Prompts

Choose appropriate directory based on technology/category
Follow the JSON schema format (see )
Include comprehensive template with placeholders
Add realistic examples with output outlines
Update

Directory Guidelines

Framework-specific: prompts/{frontend|backend}/{framework}/
General utilities: prompts/general/
Category-based: prompts/{devops|security|database|ai-ml}/

🔧 Development

# Development mode with hot reload
npm run dev

# Build for production
npm run build

# Run tests (if available)
npm test

🔐 Security

This server:

Reads prompt templates from the filesystem (read-only)
Does not execute code or make external network calls
Validates input against JSON Schema
Uses Mustache for safe template rendering

arvato-systems-romania/mcp-generic-prompts