A comprehensive collection of Model Context Protocol (MCP) servers that empower AI assistants with advanced capabilities to interact with external services, platforms, content sources, and real-time data.
MCP Series is a professional organization dedicated to developing and maintaining enterprise-grade Model Context Protocol (MCP) servers. Our mission is to extend the capabilities of Large Language Models (LLMs) through rigorously designed integrations, enabling seamless connections between AI systems and a diverse range of external services, applications, and real-time data sources. We currently maintain a growing ecosystem of eight production-ready MCP servers with more integrations in active development.
MCP is an open protocol that enables AI models to securely interact with local and remote resources through standardized server implementations. This protocol focuses on production-ready and experimental MCP servers that extend AI capabilities through file access, database connections, API integrations, and other contextual services.
| Repository | Description | Key Features | Language | Owner |
|---|---|---|---|---|
| mcp-browser-agent | Browser automation and web interaction capabilities |
|
TypeScript | @imprvhub |
| mcp-domain-availability | Domain availability checking and discovery |
|
Python | @imprvhub |
| mcp-status-observer | Real-time monitoring of major digital platforms |
|
TypeScript | @imprvhub |
| mcp-local-rag | Local RAG-like web search without APIs |
|
Python | @nkapila6 |
| mcp-claude-spotify | Comprehensive Spotify control and management |
|
TypeScript | @imprvhub |
| mcp-meme-sticky | AI-powered meme generation and sticker creation |
|
Python | @nkapila6 |
| mcp-claude-hackernews | Browse and interact with Hacker News content |
|
TypeScript | @imprvhub |
| mcp-rss-aggregator | Versatile RSS feed reader and content aggregator |
|
TypeScript | @imprvhub |
Our MCP servers are built using modern technologies and programming languages to ensure optimal performance and developer experience:
TypeScript/Node.js Servers:
- Advanced TypeScript implementation with full type safety
- Node.js runtime for efficient server operations
- npm package management for easy distribution
- Modern ES modules and async/await patterns
Python Servers:
- Python 3.10+ with modern async capabilities
- UV package manager for fast dependency resolution
- Docker containerization for seamless deployment
- FastMCP and official Python MCP SDK integration
We welcome contributions from developers passionate about expanding AI capabilities through MCP integrations. Our contribution process is designed to maintain high code quality while making it easy to get involved:
- Fork the specific repository you're interested in
- Create a feature branch (
git checkout -b feature/amazing-feature) - Develop your contribution following our coding standards
- Test thoroughly to ensure quality and compatibility
- Commit your changes (
git commit -m 'Add some amazing feature') - Push to your branch (
git push origin feature/amazing-feature) - Submit a Pull Request with comprehensive documentation
We particularly value contributions that:
- Add new platform integrations
- Enhance existing functionality
- Improve error handling and resilience
- Optimize performance across different programming languages
- Extend documentation and examples
- Support cross-platform compatibility
For TypeScript/Node.js servers:
- Follow modern TypeScript best practices
- Use ESLint and Prettier for code formatting
- Implement comprehensive error handling
- Include type definitions for all interfaces
For Python servers:
- Follow PEP 8 style guidelines
- Use type hints throughout the codebase
- Implement proper async/await patterns
- Include comprehensive docstrings
For questions, feedback, or collaboration inquiries:
- Open an issue in the relevant repository
- Check existing issues for potential solutions
- Provide detailed information when reporting problems
The MCP Series organization is an independent initiative not affiliated with Anthropic or any AI assistant providers. We develop open tools that enhance AI capabilities through the Model Context Protocol standard.
