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Triepod Memory Cache

Redis-based LLM response caching and general key-value operations via MCP protocol

Triepod Memory Cache is a sophisticated Redis-based caching system designed specifically for Large Language Model (LLM) response caching and general-purpose key-value operations. Built with the Model Context Protocol (MCP), it provides seamless integration with AI applications requiring fast, reliable response caching. The system intelligently caches LLM responses to reduce API costs, improve response times, and ensure consistent outputs for repeated queries. Beyond LLM caching, it offers comprehensive key-value storage capabilities through the MCP protocol, making it a versatile tool for AI application developers. Perfect for production AI applications requiring cost optimization through intelligent caching, reduced latency for frequently requested prompts, and reliable data persistence across sessions.

Key Metrics

2025-10-06
Last Updated
Recently maintained
Production
Status
Ready for deployment
Redis
Storage
High-performance backend

Features

LLM Response Caching

Intelligent caching system specifically optimized for Large Language Model responses to reduce costs and improve performance.

Redis Integration

High-performance Redis backend ensuring fast, reliable data storage and retrieval with sub-millisecond response times.

MCP Protocol Support

Full Model Context Protocol integration enabling seamless communication with AI applications and Claude Desktop.

Key-Value Operations

Comprehensive key-value storage capabilities for general-purpose data persistence and retrieval needs.

Technology Stack

Python
Redis
MCP Protocol
Caching