GenPark LRU TTL Multi-Tier Cache
LocalAbout GenPark LRU TTL Multi-Tier Cache
GenPark LRU TTL Multi-Tier Cache is an in-memory cache for LLM workloads, with per-key expiration, deterministic eviction, and hit, miss, and stale telemetry. It runs as an MCP server or can be imported as a library, using only the Python standard library.
Key features
- 01In-memory LRU caching
- 02Per-key TTL expiration
- 03Deterministic eviction
- 04Hit, miss, and stale telemetry
- 05Runs on the Python standard library
Use cases
- 01Caching LLM data with per-key expiration
- 02Monitoring cache hits, misses, and stale entries
MCP support
Exposes cache capabilities to MCP clients as an MCP server.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEGenPark LRU TTL Multi-Tier Cache
In-memory LRU cache with per-key TTL expiration, deterministic eviction, and hit/miss/stale telemetry for LLMs.
Part of the GenPark AI Agent Skills Ecosystem.
🌟 Key Features
- 100% Python Standard Library: Zero third-party runtime dependencies.
- MCP Native: Plugs directly into Claude Desktop, Cursor, LobeChat, and autonomous agent DAGs.
- Production Resilience: Strict schema conformance, zero data loss, enterprise hardened.
🚀 Installation & Usage
Run as an MCP server:
python mcp_server.py
Use directly as a library:
from client import *
See example_usage.py for comprehensive integration demonstrations.
📄 License
MIT License. Maintained by GenPark AI.
Comments
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