Agent Proxy System
Manages Model Context Protocol (MCP) interactions with a central proxy, intelligent agent, and a suite of mock services for seamless AI development and integration.
About
The Agent Proxy System provides a comprehensive Model Context Protocol (MCP) implementation designed to streamline AI development and integration. It features a central proxy server for routing MCP requests to various backend services, an intelligent AI agent equipped with Retrieval-Augmented Generation (RAG) capabilities, and a collection of production-ready mock MCP servers for common platforms like Filesystem, GitHub, Atlassian, and Google Drive. This system offers a scalable infrastructure to build, test, and demonstrate sophisticated AI applications leveraging the MCP standard.
Key Features
- User-friendly web interface for agent interaction
- Centralized MCP Proxy Server for routing requests
- AI Agent with Retrieval-Augmented Generation (RAG) capabilities
- Comprehensive testing suite with unit, integration, and E2E tests
- 0 GitHub stars
- Mock MCP Servers for Filesystem, GitHub, Atlassian, and Google Drive
Use Cases
- Integrating AI agents with diverse backend services via MCP
- Building scalable MCP infrastructure for AI development and integration
- Testing Model Context Protocol implementations and agent workflows
