# PyPI Query MCP Server - Prompt Templates Feature Summary ## ๐ŸŽฏ Overview Successfully implemented comprehensive MCP prompt templates for the PyPI Query MCP Server, adding structured guidance capabilities for common PyPI package analysis and decision-making scenarios. ## โœ… Completed Features ### 1. **Package Analysis Templates** - **`analyze_package_quality`** - Comprehensive package quality analysis - **`compare_packages`** - Detailed comparison of multiple packages - **`suggest_alternatives`** - Finding suitable package alternatives ### 2. **Dependency Management Templates** - **`resolve_dependency_conflicts`** - Structured dependency conflict resolution - **`plan_version_upgrade`** - Package version upgrade planning - **`audit_security_risks`** - Security risk assessment and compliance ### 3. **Migration Planning Templates** - **`plan_package_migration`** - Comprehensive migration strategy planning - **`generate_migration_checklist`** - Detailed migration checklists ## ๐Ÿ“ File Structure ``` pypi_query_mcp/ โ”œโ”€โ”€ prompts/ โ”‚ โ”œโ”€โ”€ __init__.py # Module exports โ”‚ โ”œโ”€โ”€ package_analysis.py # Package analysis templates โ”‚ โ”œโ”€โ”€ dependency_management.py # Dependency management templates โ”‚ โ””โ”€โ”€ migration_guidance.py # Migration planning templates โ”œโ”€โ”€ server.py # Updated with prompt registrations examples/ โ”œโ”€โ”€ prompt_templates_demo.py # Demonstration script tests/ โ”œโ”€โ”€ test_prompt_templates.py # Test coverage docs/ โ”œโ”€โ”€ PROMPT_TEMPLATES.md # Comprehensive documentation โ””โ”€โ”€ README.md # Updated with new features ``` ## ๐Ÿ”ง Technical Implementation ### Prompt Template Architecture - **Message-based structure**: Each template returns structured Message objects - **Parameter validation**: Using Pydantic Field annotations for robust input validation - **Async support**: All templates are async-compatible for FastMCP integration - **Type safety**: Full type annotations for better IDE support and validation ### FastMCP Integration - **Server registration**: All templates registered as MCP prompts in server.py - **Standardized naming**: Consistent naming convention for prompt functions - **Return format**: Templates return structured text prompts for LLM consumption ### Key Features - **Comprehensive guidance**: Each template provides detailed, actionable prompts - **Structured output**: Markdown-formatted prompts with clear sections and emojis - **Contextual parameters**: Rich parameter sets for customizing prompt content - **Real-world scenarios**: Templates address common PyPI package management challenges ## ๐Ÿ“– Documentation ### 1. **PROMPT_TEMPLATES.md** - Complete documentation for all 8 prompt templates - Parameter descriptions and usage examples - Integration examples for different MCP clients - Best practices and customization guidance ### 2. **Updated README.md** - Added prompt templates to feature list - Updated tool count and descriptions - Added usage examples for prompt templates - Cross-referenced detailed documentation ### 3. **Demo and Examples** - **prompt_templates_demo.py**: Interactive demonstration script - **Usage examples**: Real-world scenarios in documentation - **Client integration**: Examples for Claude Desktop, Cursor, Cline ## ๐Ÿงช Testing and Quality ### Test Coverage - **Unit tests**: Comprehensive test suite for all prompt templates - **Integration tests**: Validation of prompt structure and content - **Mock testing**: Isolated testing without external dependencies ### Code Quality - **Linting**: Passed ruff and isort checks - **Type checking**: Full type annotations and validation - **Documentation**: Comprehensive docstrings and comments ## ๐Ÿš€ Usage Examples ### In Claude Desktop ``` Use the "analyze_package_quality" prompt template to analyze the requests package ``` ### In Cursor ``` @pypi-query analyze_package_quality requests 2.31.0 ``` ### Programmatic Usage ```python from fastmcp import Client client = Client("pypi_query_mcp.server:mcp") result = await client.get_prompt("analyze_package_quality", { "package_name": "requests", "version": "2.31.0" }) ``` ## ๐ŸŽจ Template Categories ### **Analysis & Evaluation** - Quality assessment frameworks - Comparative analysis structures - Alternative evaluation criteria ### **Problem Solving** - Dependency conflict resolution strategies - Security audit methodologies - Upgrade planning frameworks ### **Project Management** - Migration planning templates - Checklist generation - Timeline and resource planning ## ๐Ÿ”ฎ Benefits ### **For Developers** - **Structured guidance**: Clear frameworks for package decisions - **Time saving**: Pre-built templates for common scenarios - **Best practices**: Incorporates industry standards and methodologies - **Consistency**: Standardized approach to package analysis ### **For Teams** - **Knowledge sharing**: Consistent evaluation criteria across team members - **Documentation**: Built-in documentation templates for decisions - **Risk management**: Structured risk assessment frameworks - **Planning**: Comprehensive migration and upgrade planning ### **For Projects** - **Quality assurance**: Systematic package evaluation processes - **Security**: Built-in security assessment templates - **Maintenance**: Structured upgrade and migration planning - **Compliance**: Templates for regulatory and compliance requirements ## ๐ŸŽฏ Integration Ready The prompt templates are now fully integrated into the PyPI Query MCP Server and ready for use in any MCP-compatible client: - โœ… **Claude Desktop** - Full prompt template support - โœ… **Cursor** - Command palette integration - โœ… **Cline** - Interactive prompt access - โœ… **Windsurf** - Built-in template support - โœ… **Custom clients** - Programmatic API access ## ๐Ÿ“Š Impact This feature significantly enhances the PyPI Query MCP Server by: 1. **Expanding capabilities** from simple queries to comprehensive guidance 2. **Improving user experience** with structured, actionable prompts 3. **Supporting decision-making** with proven frameworks and methodologies 4. **Enabling best practices** through built-in templates and guidance 5. **Facilitating team collaboration** with standardized evaluation criteria The prompt templates transform the server from a data provider into a comprehensive PyPI package management advisor, making it an essential tool for Python developers and teams.