4bdf38d455
- Implement standard MCP prompt workflow with template variables
- Use {{parameter_name}} placeholders instead of direct string interpolation
- Add proper parameter replacement in server prompt registrations
- Update templates to return template strings with placeholders
- Follow MCP workflow: load template → parameter replacement → return final prompt
- Update documentation to reflect standard MCP workflow implementation
- Remove TEMPLATES_USE environment variable as requested
- Maintain all existing functionality while improving MCP compliance
Signed-off-by: longhao <hal.long@outlook.com>
173 lines
6.4 KiB
Markdown
173 lines
6.4 KiB
Markdown
# PyPI Query MCP Server - Prompt Templates Feature Summary
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## 🎯 Overview
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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.
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## ✅ Completed Features
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### 1. **Package Analysis Templates**
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- **`analyze_package_quality`** - Comprehensive package quality analysis
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- **`compare_packages`** - Detailed comparison of multiple packages
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- **`suggest_alternatives`** - Finding suitable package alternatives
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### 2. **Dependency Management Templates**
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- **`resolve_dependency_conflicts`** - Structured dependency conflict resolution
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- **`plan_version_upgrade`** - Package version upgrade planning
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- **`audit_security_risks`** - Security risk assessment and compliance
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### 3. **Migration Planning Templates**
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- **`plan_package_migration`** - Comprehensive migration strategy planning
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- **`generate_migration_checklist`** - Detailed migration checklists
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## 📁 File Structure
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```
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pypi_query_mcp/
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├── prompts/
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│ ├── __init__.py # Module exports
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│ ├── package_analysis.py # Package analysis templates
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│ ├── dependency_management.py # Dependency management templates
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│ └── migration_guidance.py # Migration planning templates
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├── server.py # Updated with prompt registrations
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examples/
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├── prompt_templates_demo.py # Demonstration script
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tests/
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├── test_prompt_templates.py # Test coverage
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docs/
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├── PROMPT_TEMPLATES.md # Comprehensive documentation
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└── README.md # Updated with new features
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```
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## 🔧 Technical Implementation
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### Prompt Template Architecture
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- **Message-based structure**: Each template returns structured Message objects
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- **Parameter validation**: Using Pydantic Field annotations for robust input validation
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- **Async support**: All templates are async-compatible for FastMCP integration
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- **Type safety**: Full type annotations for better IDE support and validation
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### FastMCP Integration
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- **Server registration**: All templates registered as MCP prompts in server.py
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- **Standardized naming**: Consistent naming convention for prompt functions
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- **Return format**: Templates return structured text prompts for LLM consumption
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### Key Features
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- **Comprehensive guidance**: Each template provides detailed, actionable prompts
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- **Structured output**: Markdown-formatted prompts with clear sections and emojis
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- **Contextual parameters**: Rich parameter sets for customizing prompt content
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- **Real-world scenarios**: Templates address common PyPI package management challenges
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## 📖 Documentation
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### 1. **PROMPT_TEMPLATES.md**
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- Complete documentation for all 8 prompt templates
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- Parameter descriptions and usage examples
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- Integration examples for different MCP clients
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- Best practices and customization guidance
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### 2. **Updated README.md**
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- Added prompt templates to feature list
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- Updated tool count and descriptions
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- Added usage examples for prompt templates
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- Cross-referenced detailed documentation
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### 3. **Demo and Examples**
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- **prompt_templates_demo.py**: Interactive demonstration script
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- **Usage examples**: Real-world scenarios in documentation
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- **Client integration**: Examples for Claude Desktop, Cursor, Cline
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## 🧪 Testing and Quality
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### Test Coverage
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- **Unit tests**: Comprehensive test suite for all prompt templates
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- **Integration tests**: Validation of prompt structure and content
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- **Mock testing**: Isolated testing without external dependencies
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### Code Quality
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- **Linting**: Passed ruff and isort checks
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- **Type checking**: Full type annotations and validation
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- **Documentation**: Comprehensive docstrings and comments
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## 🚀 Usage Examples
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### In Claude Desktop
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```
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Use the "analyze_package_quality" prompt template to analyze the requests package
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```
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### In Cursor
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```
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@pypi-query analyze_package_quality requests 2.31.0
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```
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### Programmatic Usage
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```python
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from fastmcp import Client
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client = Client("pypi_query_mcp.server:mcp")
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result = await client.get_prompt("analyze_package_quality", {
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"package_name": "requests",
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"version": "2.31.0"
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})
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```
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## 🎨 Template Categories
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### **Analysis & Evaluation**
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- Quality assessment frameworks
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- Comparative analysis structures
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- Alternative evaluation criteria
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### **Problem Solving**
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- Dependency conflict resolution strategies
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- Security audit methodologies
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- Upgrade planning frameworks
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### **Project Management**
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- Migration planning templates
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- Checklist generation
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- Timeline and resource planning
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## 🔮 Benefits
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### **For Developers**
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- **Structured guidance**: Clear frameworks for package decisions
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- **Time saving**: Pre-built templates for common scenarios
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- **Best practices**: Incorporates industry standards and methodologies
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- **Consistency**: Standardized approach to package analysis
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### **For Teams**
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- **Knowledge sharing**: Consistent evaluation criteria across team members
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- **Documentation**: Built-in documentation templates for decisions
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- **Risk management**: Structured risk assessment frameworks
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- **Planning**: Comprehensive migration and upgrade planning
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### **For Projects**
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- **Quality assurance**: Systematic package evaluation processes
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- **Security**: Built-in security assessment templates
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- **Maintenance**: Structured upgrade and migration planning
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- **Compliance**: Templates for regulatory and compliance requirements
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## 🎯 Integration Ready
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The prompt templates are now fully integrated into the PyPI Query MCP Server and ready for use in any MCP-compatible client:
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- ✅ **Claude Desktop** - Full prompt template support
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- ✅ **Cursor** - Command palette integration
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- ✅ **Cline** - Interactive prompt access
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- ✅ **Windsurf** - Built-in template support
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- ✅ **Custom clients** - Programmatic API access
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## 📊 Impact
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This feature significantly enhances the PyPI Query MCP Server by:
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1. **Expanding capabilities** from simple queries to comprehensive guidance
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2. **Improving user experience** with structured, actionable prompts
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3. **Supporting decision-making** with proven frameworks and methodologies
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4. **Enabling best practices** through built-in templates and guidance
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5. **Facilitating team collaboration** with standardized evaluation criteria
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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.
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