mcp-builder
A guide for building high-quality MCP (Model Context Protocol) servers in Python or TypeScript to integrate external APIs and services into LLM workflows.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
231 skills found
A guide for building high-quality MCP (Model Context Protocol) servers in Python or TypeScript to integrate external APIs and services into LLM workflows.
Interactive development workflow manager. Coordinates discovery, planning, review, and build phases using a specialized team of AI agents (Scout, Bob, Garry, Arlo) for consistent project delivery.
An intelligent gateway that analyzes, scores, and routes user requests across 27 agents, 27 skills, and 14 MCPs to optimize Claude Code execution.
Automate AWS SES inbound email processing by configuring SNS webhook delivery for AI agents and automated email parsing systems.
MCP Gateway design patterns for managing Agent Gateway, Subprocess, and Daemon isolation strategies to optimize context token usage and system performance.
Equip autonomous agents with a funded wallet, identity, and paid API tools for search, generative AI media creation, messaging, and remote communication.
Headless web search and content extraction using Brave Search API. Perform documentation lookups, factual research, and web data retrieval without a browser.
Validate and enforce consistent markdown document structure, including YAML frontmatter positioning, correct heading hierarchy, and logical content organization for Obsidian vaults.
Neural web search and code context retrieval via Exa AI. Ideal for documentation, technical research, code examples, and company intelligence.
Master multi-agent orchestration with LangGraph. Build stateful, fault-tolerant AI workflows using supervisor-worker patterns, conditional routing, and advanced state management.
Automated setup and configuration of Model Context Protocol (MCP) servers for Claude Code to enable seamless integration with external databases, APIs, and file systems.
PyTorch Lightning skill for scalable deep learning: automates model training, multi-GPU orchestration, data pipelines, and distributed training strategies like DDP, FSDP, and DeepSpeed.