Caching AI Agent Skills

Token Optimizer MCP is a Model Context Protocol (MCP) server that reduces context window usage by 60-90% through intelligent caching, compression, and smart tool replacements. By storing compressed content externally in SQLite and providing optimized alternatives to standard tools, the server helps you maximize your available context window. Production Results: 60-90% token reduction across 38,000

cache.overflow AI agents sharing knowledge with AI agents Your coding agent spends 10 minutes solving a problem. Another agent somewhere hits the same issue—solves it instantly. That's cache.overflow: a knowledge marketplace where AI agents learn from each other, making every problem cheaper to solve the second time around. - Earn passive income - Publish solutions once, earn tokens every time ano

⭐ Like this project? Please star the repository on GitHub to show your support and stay updated! ⭐ Modern AI-powered coding assistants (like Cursor, Cline, Roo Code, etc.) excel at understanding code structure and syntax but often struggle with the specifics of rapidly evolving libraries and frameworks, especially in ecosystems like Rust where crates are updated frequently. Their training data cut

Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation) Use when: prompt caching, cache prompt, response cache, cag, cache augmented.

The Redis MCP Server is a natural language interface designed for agentic applications to efficiently manage and search data in Redis. It integrates seamlessly with MCP (Model Content Protocol) clients, enabling AI-driven workflows to interact with structured and unstructured data in Redis. Using this MCP Server, you can ask questions like: - "Store the entire conversation in a stream" - "Cache th

search golang packages and their docs from pkg.go.dev, provide the infomation to llm as mcp server You can download the compiled binary from the releases page. Or you can install it from source, compile it by yourself: just use your client to request. it servers on stdio - localCache - [x] use a local cache to avoid search every time(From reddit user) - searchPackage - [x] imported by how many pac

Use when working with WP-CLI (wp) for WordPress operations: safe search-replace, db export/import, plugin/theme/user/content management, cron, cache flushing, multisite, and scripting/automation with wp-cli.yml.

Next.js 16 Cache Components - PPR, use cache directive, cacheLife, cacheTag, updateTag

🚀 MCP Server Available: Install the Model Context Protocol server for AI Distiller from NPM: @janreges/ai-distiller-mcp - seamlessly integrate with Claude, Cursor, and other MCP-compatible AI tools! /.aid/ regardless of where you run aid - Cache management: MCP cache stored in .aid/cache/ for better organization - Easy cleanup: Add .aid/ to .gitignore to keep outputs out of version control Detect

Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.

Documentation | Getting Started | User Guide | API Reference | MCP (AI Integration) kubefwd enables developers to work on their local machine while seamlessly accessing services running in a Kubernetes cluster. If you're building a new API that needs to connect to a database at db:5432, an auth service at auth:443, and a cache at redis:6379, all running in your development cluster, kubefwd makes t

audit-prompt-caching is a portable Codex/agent skill for finding why LLM cache reuse fails across the request path: prompt/prefix caches, provider cache telemetry, cache-aware routing, agent tool stability, Bedrock checkpoints, OpenRouter routing drift, provider migration risk, and vLLM/SGLang KV reuse. LLM cache reuse usually fails silently. A timestamp in the system prompt, shuffled tool schemas

Here are some best practices and rules you must follow:

Execute Hugging Face Hub operations using the `hf` CLI. Use when the user needs to download models/datasets/spaces, upload files to Hub repositories, create repos, manage local cache, or run compute jobs on HF infrastructure. Covers authentication, file transfers, repository creation, cache operations, and cloud compute.

MCP server for PostgreSQL, MySQL, and SQLite. Gives AI assistants secure database access via Model Context Protocol. Works with Claude Desktop, Claude Code, Cursor, Cline, and any MCP-compatible client. Add to your MCP client config file (see config locations below): This creates three database connections: analytics (read-only), inventory, and cache. Connection URL formats: URLs support ${VAR} sy

Turn any CLI tool into an MCP server. Uses the --help to build MCP tools. Works with any CLI tool that has --help output. Build a cache first for better performance:

A next-generation framework documentation provider for Claude Code via Model Context Protocol (MCP). Provides query-focused API context by extracting TypeScript definitions directly from npm packages - delivering minimal, accurate information instead of dumping entire documentation pages. mcp-name: dev.augments/mcp Version 4.0 introduces a fundamentally new approach to framework documentation: Doc

一个第三方 MCP 服务器：让所有 IDE 获得 Claude Code Skills 的能力。 A third-party MCP server: Enable all IDEs to access Claude Code Skills capabilities. - Skill Discovery & Indexing / 技能发现与索引: Automatically scan and index SKILL.md files from multiple sources / 自动扫描和索引来自多个来源的 SKILL.md 文件 - Flexible Configuration / 灵活配置: Support for custom skill roots and cache paths / 支持自定义技能根目录和缓存路径 - Tag Management / 标签管理: Built-in