Local
Implements an advanced AI agent system with intelligent tool orchestration, multi-LLM support, and enterprise-grade reliability for scalable Model Context Protocol architectures.
소개
Local is a robust, production-ready AI agent system designed to overcome challenges in scaling Model Context Protocol (MCP) architectures. It integrates cutting-edge patterns such as semantic tool orchestration, multi-layer caching, and circuit breaker patterns to ensure high performance and reliability. With support for multiple Large Language Models (LLMs) and innovative features like MCP-Zero Active Discovery for significant token reduction and Hierarchical Semantic Routing for optimal tool selection, Local streamlines the creation of efficient, LLM-friendly environments.
주요 기능
- Hierarchical Semantic Routing for optimal two-stage tool selection from vast options
- 0 GitHub stars
- MCP-Zero Active Discovery for 98% token reduction via autonomous tool requests
- Multi-LLM Support with a unified gateway for diverse LLM providers
- Multi-Layer Caching (in-memory, distributed, semantic similarity) for reduced latency
- Elastic Circuit De-Constructor for graceful degradation and partial functionality retention
사용 사례
- Orchestrating AI tools with semantic search and intelligent routing
- Integrating AI agents with diverse knowledge bases and LLM providers
- Building and scaling advanced AI agent systems
