This MCP server provides caching and memoization tools for AI agents, enabling analysis, generation, simulation, and optimization of caching strategies across various layers.
From the registry: Cache headers, CDN, LRU simulation for AI agents
$ git clone https://github.com/rog0x/mcp-cache-tools && cd mcp-cache-tools && npm install && npm run buildPlease install the `cache` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Clone and build** — Clone rog0x/mcp-cache-tools and build with npm — no published package. Run: `git clone https://github.com/rog0x/mcp-cache-tools && cd mcp-cache-tools && npm install && npm run build` (https://github.com/rog0x/mcp-cache-tools)
Canonical MCP server config (stdio transport):
- command: `node`
- args: ["<path-to-mcp-cache-tools>/dist/index.js"]
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Persistent codebase knowledge graph. Survives session restarts and context compaction.
Validate oh-my-posh configurations and segment snippets against the official schema.