Dicklesworthstone_llm_gateway_mcp_server
0
LLM Gateway is an MCP server designed to optimize AI task delegation by connecting high-capability AI agents with cost-effective models. It reduces the operational cost by intelligently routing tasks to suitable models, ensuring efficient processing while maintaining high output quality.
LLM Gateway MCP Server
LLM Gateway is a Model Context Protocol (MCP) server that enables intelligent task delegation from advanced AI agents like Claude 3.7 Sonnet to more cost-effective models such as Gemini Flash 2.0 Lite. It provides a unified interface to multiple LLM providers while optimizing for cost, performance, and quality.
Key Features
- AI-to-AI Task Delegation: Allows advanced AI models to delegate tasks to cheaper models, achieving high performance at reduced costs.
- Cost Optimization: Reduces API costs through strategic task routing and advanced caching mechanisms.
- Provider Abstraction: Offers a consistent API for multiple providers, facilitating easy integration and provider swap.
- Document Processing: Supports efficient processing of large documents and extraction of structured data.
- MCP Protocol Integration: Exposes functionality via standardized MCP tools, enabling seamless AI-to-AI delegation.
- Advanced Caching: Implements multiple caching strategies, including semantic similarity and task-aware caching.
Usage Examples
- AI Workflow: Claude delegates document summarization to Gemini Flash, reducing cost by 90%.
- Multi-Provider Comparison: Compare outputs from various LLMs for decision-making.
- Cost-Optimized Workflow: Execute multi-stage workflows with cost-aware model selection.
Getting Started
Installation
- Install using
uvand clone the repository.
Running the Server
- Start the server using Python or Docker Compose.
Advanced Configuration
- Configure server, logging, cache, and provider settings via environment variables.
Deployment Considerations
- Use a reverse proxy and a process manager for reliable operations.