The MCP Prompts Server is a tool for managing and applying AI prompts and templates with robust storage and orchestration capabilities. With this server, you can:
Store and retrieve prompts: Add new prompts with metadata and retrieve them by ID
Create and manage templates: Define templates with variables for consistent prompting
Apply variables to templates: Dynamically fill templates with specific values
Filter and sort prompts: List prompts by tags, category, or search terms with pagination
Update and delete prompts: Modify or remove existing prompts
Access multiple storage backends: Use file storage, PostgreSQL, or MDC format
Integrate with AI tools: Seamlessly work with platforms like Claude
Project orchestration: Manage complex AI systems and workflows
Support multi-format prompts: Work with JSON, MDC, PGAI, and Template formats
Health check endpoints: Monitor system status
Supports deployment using Docker and Docker Compose for containerized deployment
Built on Node.js with support for Node.js 18 or later
Provides integration with PostgreSQL databases for storing prompts, with export/import functionality and synchronization between file storage and database
Built using TypeScript, as indicated by the project structure and build process
MCP Prompts Server
A robust, extensible server for managing, versioning, and serving prompts and templates for LLM applications, built on the Model Context Protocol (MCP).
🚀 Features
Dual Mode Operation
- HTTP Mode - Traditional REST API server
- MCP Mode - Model Context Protocol server for AI assistants
MCP Tools (7 Available)
add_prompt
- Add new prompts to collectionget_prompt
- Retrieve prompts by IDlist_prompts
- List prompts with filteringupdate_prompt
- Update existing promptsdelete_prompt
- Remove promptsapply_template
- Apply variables to template promptsget_stats
- Get prompt statistics
Pre-loaded Templates
- Code Review Assistant
- Documentation Writer
- Bug Analyzer
- Architecture Reviewer
- Test Case Generator
📦 Installation
🎯 Quick Start
HTTP Mode
MCP Mode
🔧 Cursor Integration
- Configure Cursor MCP:
Add to
.cursor/mcp.json
: - Restart Cursor to load the MCP server
- Use in Cursor:
- The MCP tools will be available in Cursor's AI assistant
- You can ask Cursor to manage prompts using natural language
🐳 Docker Support
Build MCP Docker Image
Run with Docker Compose
View Logs
📚 Documentation
- MCP_README.md - Comprehensive MCP usage guide
- API Documentation - Full API reference
- Examples - Usage examples and configurations
🛠 Development
Prerequisites
- Node.js >= 20.0.0
- pnpm >= 9.0.0
Setup
Available Scripts
📊 Project Structure
🔍 Testing
MCP Server Testing
HTTP Server Testing
📈 Usage Examples
Using MCP Tools
List All Prompts
<<<<<<< HEAD
Build Issues
TypeScript Path Resolution Errors:
SWC Build Failures:
Workspace Dependency Issues:
Missing Modules or Types:
- Ensure you have built
@mcp-prompts/core
first - Check that all
dist/
directories are up to date - If you change the shared config or move files, clean all
dist/
directories and rebuild
Runtime Issues
Common Issues:
- If you see errors about missing modules or types, ensure you have built
@mcp-prompts/core
first and that alldist/
directories are up to date. - If you change the shared config or move files, clean all
dist/
directories and rebuild.
Architecture
Hexagonal Architecture (Ports & Adapters)
MCP Prompts follows a clean hexagonal architecture pattern:
- Core: Pure domain logic without infrastructure dependencies
- Ports: Interfaces defined in core package
- Adapters: Infrastructure implementations in adapter packages
- Apps: Composition and configuration in apps folder
Directory Structure
Development
Build Commands
Package-specific Commands
Testing
- Vitest for unit tests
- Playwright for e2e tests
- Coverage > 90% for core packages
- Integration tests for adapters
API Reference
For detailed API documentation, see:
References
- Turborepo TypeScript Monorepo Guide
- Separate tsconfig for builds
- Hexagonal Architecture: Wikipedia
MCP Specification
Apply Template
Add New Prompt
🌟 Features
- Template Variables - Use
{{variable}}
syntax for dynamic content - Tag System - Organize prompts with tags for easy filtering
- Metadata Support - Add categories, difficulty, time estimates
- Version Control - Track prompt versions and changes
- Error Handling - Comprehensive error handling and logging
- TypeScript - Full TypeScript support with type definitions
- Docker Ready - Containerized deployment support
🤝 Contributing
- Fork the repository
- Create a feature branch
- Implement your changes
- Add tests if applicable
- Submit a pull request
📄 License
MIT License - see LICENSE file for details.
🆘 Support
- Issues: GitHub Issues
- Documentation: MCP_README.md
- Examples: examples/
Version: 3.0.8
Status: ✅ Production Ready
MCP Support: ✅ Full Implementation
Cursor Integration: ✅ Ready
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Enables creation, management, and templating of prompts through a simplified SOLID architecture, allowing users to organize prompts by category and fill in templates at runtime.
- Table of Contents
- Features
- Installation
- Configuration
- Usage
- Prompt Format
- Multi-Format Prompt Support
- Storage Adapters
- Docker Deployment
- Development
- Release Process
- Changelog
- Best Practices
- License
Related Resources
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