@pagopa/dx-mcpprompts

@pagopa/dx-mcpprompts

A TypeScript package for managing Markdown-based prompts with YAML frontmatter, designed for AI assistants and the Model Context Protocol (MCP). This package provides a self-contained collection of validated prompts that can be consumed programmatically or served via MCP servers.

Creating New Prompts

1. File Structure

Create a new Markdown file in src/prompts/ with this structure:

---
id: "unique-prompt-id"
title: "Human Readable Title"
description: "Brief description of what this prompt does"
category: "terraform|security|infrastructure|development"
enabled: true
tags: ["tag1", "tag2", "tag3"]
examples:
  - "Example usage scenario 1"
  - "Example usage scenario 2"
arguments:
  - name: "argument_name"
    description: "Description of what this argument does"
    required: true
  - name: "optional_argument"
    description: "Optional argument with default"
    required: false
    default: "default-value"
mode: "agent|assistant|completion"
tools: ["tool1", "tool2"]
---

# Your Prompt Title

Your prompt content goes here using **Markdown formatting**.

You can reference arguments using template variables: {{argument_name}}

## Instructions

1. Be specific and clear in your instructions
2. Use structured format with headings and lists
3. Include examples where helpful
4. Reference tools that should be used: {{tools}}

Expected outcome: {{optional_argument}}

2. Frontmatter Schema

Required Fields

• id: Unique identifier (kebab-case, no spaces)
• title: Human-readable title for the prompt
• description: Brief description of the prompt's purpose
• category: Main category (terraform, security, infrastructure, development)
• enabled: Boolean flag to enable/disable the prompt

Optional Fields

• tags: Array of tags for filtering and search
• examples: Array of example use cases or scenarios
• arguments: Array of input parameters (see Argument Schema below)
• mode: Execution mode hint (agent, assistant, completion)
• tools: Array of tools the prompt expects to use

Argument Schema

Each argument in the arguments array supports:

- name: "parameter_name" # Used in {{parameter_name}} substitution
  description: "What this does" # Human-readable description
  required: true # Whether argument is mandatory (default: false)
  default: "fallback_value" # Default value if not provided (optional)

3. Template Variables

Use double curly braces for variable substitution:

• Basic: {{variable_name}} - replaced with argument values
• With defaults: If argument not provided, uses default from frontmatter
• Fallback: Missing variables without defaults become empty strings

Example:

Hello {{name}}, welcome to {{environment}}!
Version: {{version}}

4. Validation

All prompts are automatically validated when loaded:

• ✅ Frontmatter structure validation using Zod schemas
• ✅ Required field presence checking
• ✅ Type validation for all fields
• ✅ Content presence validation

Invalid prompts are logged and excluded from the catalog, allowing other prompts to continue working.

Development Workflow

Adding a New Prompt

• Create src/prompts/my-new-prompt.md
• Add frontmatter with required fields
• Write content using template variables
• Test locally:

  cd packages/mcp-prompts
  pnpm test
  pnpm build
  

Best Practices

• Use descriptive IDs: migrate-terraform-module not migrate
• Provide clear descriptions: Help users understand when to use the prompt
• Include examples: Show typical use cases in the frontmatter
• Use appropriate categories: Helps with organization and filtering
• Add default values: For optional arguments to improve UX
• Keep content focused: One clear purpose per prompt
• Use proper Markdown: Headers, lists, code blocks for clarity

Package Architecture

• Location: packages/mcp-prompts/src/prompts/
• Build: Prompts are copied to dist/prompts/ during build
• Runtime: Auto-detection of src vs dist for development/production
• Validation: Zod schemas ensure type safety and data integrity
• Logging: Uses LogTape for structured logging (configure in your app)

Integration

This package is consumed by:

• MCP Server (apps/mcpserver): Exposes prompts to AI tools via MCP protocol
• Documentation Website (apps/website): Displays prompt catalog and examples