Local

关于

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.

主要功能

• Hierarchical Semantic Routing for optimal two-stage tool selection from vast options
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• 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

使用案例

• 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