MCPheonix

What is MCPheonix? MCPheonix is a simplified implementation of the Model Context Protocol (MCP) server using Elixir's Phoenix Framework, designed to facilitate intelligent, self-healing, distributed AI event systems. How to use MCPheonix? To use MCPheonix, clone the repository, install dependencies, configure Cloudflare integration, and start the server. Detailed instructions are provided in the documentation. Key features of MCPheonix? Real-time notifications via Server-Sent Events (SSE) JSON-RPC endpoint for client requests Event publish/subscribe mechanism Self-healing distributed architecture with Cloudflare Durable Objects Extensible architecture for custom MCP servers Use cases of MCPheonix? Building resilient AI applications that require real-time data processing. Integrating multiple AI models with a unified interface. Developing applications that need to maintain state across distributed systems. FAQ from MCPheonix? What is the Model Context Protocol? The Model Context Protocol is a standard for enabling AI models to interact with application data and functionality. Is MCPheonix suitable for production use? Yes, MCPheonix is designed for production environments with its self-healing capabilities. What are the prerequisites for running MCPheonix? You need Elixir, Erlang, Phoenix, Python, Node.js, and a Cloudflare account for integration.

As an MCP (Model Context Protocol) server, MCPheonix enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use MCPheonix, clone the repository, install dependencies, configure Cloudflare integration, and start the server. Detailed instructions are provided in the documentation. Key features of MCPheonix? Real-time notifications via Server-Sent Events (SSE) JSON-RPC endpoint for client requests Event publish/subscribe mechanism Self-healing distributed architecture with Cloudflare Durable Objects Extensible architecture for custom MCP servers Use cases of MCPheonix? Building resilient AI applications that require real-time data processing. Integrating multiple AI models with a unified interface. Developing applications that need to maintain state across distributed systems. FAQ from MCPheonix? What is the Model Context Protocol? The Model Context Protocol is a standard for enabling AI models to interact with application data and functionality. Is MCPheonix suitable for production use? Yes, MCPheonix is designed for production environments with its self-healing capabilities. What are the prerequisites for running MCPheonix? You need Elixir, Erlang, Phoenix, Python, Node.js, and a Cloudflare account for integration.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.