mcp-development
Guidance for Model Context Protocol (MCP) server development, including tool design, resource handling, and AI/ML integration patterns.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
167 skills found
Guidance for Model Context Protocol (MCP) server development, including tool design, resource handling, and AI/ML integration patterns.
Expert skill for building and maintaining AI agents using the Claude Agent SDK, covering architecture, tool integration, MCP servers, and agentic workflows.
Process and generate multimedia with Google Gemini. Analyze audio, images, videos, and PDFs with high-context windows. Supports transcription, visual QA, OCR, and AI-driven image creation.
Dynamic meta-router for managing and orchestrating multi-domain AI coding agent skills across plugins and projects.
Provides comprehensive knowledge on Zed Editor and the Agent Client Protocol (ACP), including AI agent integration, performance tuning, and configuration for professional development workflows.
An AI-driven framework for crafting bespoke, authentic portfolio websites from scratch. Guides agents through research, design, and code implementation to build unique developer and professional sites.
MPC-based multi-chain wallet SDK and CLI for AI agents and developers. Perform secure, threshold-signed crypto operations (send, swap, sign) across 40+ blockchains without seed phrases.
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Official AIRIOT development toolkit for building React applications with TypeScript, shadcn/ui, and integrated real-time platform capabilities.
Orchestrate complex multi-agent swarms with topologies like mesh, hierarchical, and star for research, development, and testing workflows.
A standardized workflow for converting raw PM notes, workshops, or rough drafts into polished, validated, and repository-compliant AI skills.
A toolkit for building robust LLM integrations: API patterns, streaming, function calling, RAG pipelines, and cost-effective model routing.