Lru Caching With Differentiated Ttl By Content Type

via “result caching with configurable ttl and eviction policies”

Self-hardening prompt injection detector with multi-layer defense.

Unique: Implements configurable in-memory caching with multiple eviction policies (LRU, LFU, FIFO) and per-request cache bypass options, allowing developers to balance latency, cost, and memory usage; cache key includes configuration state to prevent incorrect hits when settings change

vs others: More sophisticated than simple TTL-based caching by supporting multiple eviction policies and configuration-aware cache keys; reduces API costs for repetitive workloads without requiring external cache infrastructure

MCP server for Apple Developer Documentation - Search iOS/macOS/SwiftUI/UIKit docs, WWDC videos, Swift/Objective-C APIs & code examples in Claude, Cursor & AI assistants

Unique: Differentiates cache TTL by content type (10 min for dynamic search results vs 1 hour for stable framework indexes vs 2 hours for WWDC video data) rather than using uniform cache duration, optimizing for the actual update frequency of each data source

vs others: More sophisticated than simple TTL caching because it recognizes that different documentation types have different freshness requirements, and more efficient than no caching because it reduces API calls while respecting content volatility

via “adaptive ttl caching with 50mb lru eviction and hit tracking”

Clean, LLM-optimized Reddit MCP server. Browse posts, search content, analyze users. No fluff, just Reddit data.

Unique: Adaptive TTL (2-30 min range) with hit tracking automatically tunes cache freshness vs hit rate — most Reddit API clients use fixed TTLs (5-10 min) without learning from access patterns

vs others: Reduces API calls by 30-50% vs no caching while maintaining data freshness, with automatic tuning eliminating manual TTL configuration that competitors require

via “intelligent-caching-with-content-hashing”

TypeScript bridge for recursive-llm: Recursive Language Models for unbounded context processing with structured outputs

Unique: Uses content hashing for automatic cache key generation rather than explicit cache management, enabling transparent caching without modifying application logic

vs others: More automatic than manual cache key management and supports distributed backends, whereas simple in-memory caches don't scale to multi-worker systems