Memory Cache
Createdtosin2013
Reduces language model token consumption by efficiently caching data between interactions.
About
Memory Cache Server minimizes token usage for language models by caching data between interactions. Working seamlessly with any Model Context Protocol (MCP) client, it automatically stores and retrieves frequently accessed data like file contents and computation results. Configuration options include setting limits on cache size, time-to-live (TTL), and update intervals, allowing for fine-tuning to optimize performance and token savings, all without requiring any manual intervention during interactions.
Key Features
- Automatic caching of data between language model interactions
- Reduces token consumption for repeated operations
- Configurable cache limits and TTL settings
- Automatic cache management (storage, retrieval, removal)
- Tracks cache effectiveness through statistics
Use Cases
- Performing calculations or analysis multiple times
- Reading the same file multiple times
- Accessing the same data frequently