Magg
Manages and aggregates multiple Model Context Protocol (MCP) servers, allowing large language models to dynamically extend their capabilities.
About
Magg acts as a central hub for managing and aggregating various Model Context Protocol (MCP) servers. It empowers large language models (LLMs) to autonomously discover, add, configure, and manage their own capabilities at runtime. Functioning much like a 'package manager for LLM tools', Magg enables AI assistants to install and manage diverse functionalities on demand, providing a unified access point for a wide array of tools and services.
Key Features
- Smart configuration of servers from just a URL using MCP sampling
- Automatic tool proxying with configurable prefixes for integrated tools
- Support for multiple MCP transport mechanisms including stdio and HTTP
- 1 GitHub stars
- Self-service tool management for LLMs to add new MCP servers
- Persistent configuration of server settings across sessions
Use Cases
- Enabling large language models to autonomously discover and integrate new capabilities
- Allowing AI assistants to dynamically extend their functionalities at runtime, similar to a package manager
- Providing a unified interface for managing and aggregating tools from various MCP servers