Ib Cache Server

A Model Context Protocol (MCP) server focused on efficient data caching between language model interactions, optimizing token usage and reducing redundant calls.

• Source: GitHub Repository
• Category: MCP Middleware Orchestration
• Tags: caching, performance, context-management, ai-integration

Features

• Automatic Data Caching: Transparently caches data between language model (token-based) interactions for any MCP client and language model.
• Reduces Token Consumption: Stores file contents, computation results, and frequently accessed data to minimize repeated token usage.
• Configurable Cache Management:
  • maxEntries: Maximum number of items in the cache (default: 1000).
  • maxMemory: Maximum memory usage for cache (default: 100MB).
  • defaultTTL: Time-to-live for cache entries (default: 1 hour).
  • checkInterval: Frequency for cache cleanup (default: 1 minute).
  • statsInterval: Interval for updating cache statistics (default: 30 seconds).
• Multiple Configuration Methods: Configure via config.json or environment variables, with support for custom config file locations.
• Cache Management Policies:
  • Removes oldest/unused entries when limits are exceeded.
  • Automatic expiration of stale data based on TTL.
  • Least recently used (LRU) eviction when memory or entry limits are hit.
• Statistics and Monitoring: Tracks cache hit/miss rates and usage statistics for performance monitoring.
• Optimized for Performance: Improves response times for repeated operations (such as reading files or performing repeated computations).
• No Manual Intervention Needed: Caching is fully automatic; no changes to client code required.
• Compatible with Any MCP Client: Integrates with any client that supports Model Context Protocol.
• Support for Customization: Easily adjust TTL, memory, and entry limits based on workload needs.

Usage Examples

• Caching file reads to speed up repeated file access.
• Caching computation results to avoid redundant processing.
• Serving frequently accessed project navigation data from cache.

Pricing

No pricing information provided. The project is open-source and available for use via the GitHub repository.