mcp-client
Universal MCP client for connecting to any MCP server with progressive disclosure. Wraps MCP servers as skills to prevent context window bloat from tool definitions. Use for Zapier, GitHub, sequential thinking, and file operations.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
184 skills found
Universal MCP client for connecting to any MCP server with progressive disclosure. Wraps MCP servers as skills to prevent context window bloat from tool definitions. Use for Zapier, GitHub, sequential thinking, and file operations.
Full-stack automated paper writing pipeline from research narrative to polished LaTeX/PDF.
Manage the full lifecycle of blog posts, from initial concept and outlining to drafting and editorial refinement for Nuxt/Vue developers.
A toolkit for developing and bundling complex, multi-component React/TypeScript web artifacts using Vite, Tailwind CSS, and shadcn/ui.
Automate your daily Milan news digest with this Python-based briefing tool. Supports weather, strikes, world/AI/Italian news, and event scraping, featuring deduplication, RSS/API pipeline management, and AI-agent ready scheduling.
A runtime skill discovery engine for AI agents. Search and retrieve specialized agent skills (SKILL.md) on-demand via REST API or MCP to inject procedural knowledge into your agent's context.
An all-in-one Chinese daily utility toolkit: weather, currency exchange, news, and package tracking. Zero configuration, no API keys required.
Enterprise-grade multi-agent swarm orchestration, event-driven workflow automation, and intelligent agent coordination for Claude Code.
Perform a structured 8-factor conversion rate optimization (CRO) audit of any landing page to identify friction points and opportunities for growth.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Analyze project codebases to generate architecture documentation, coding standards, and development practices for AI onboarding.
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.