ae-mcp
Automate Adobe After Effects tasks using the Model Context Protocol. Manage compositions, layers, keyframes, effects, and expressions for motion graphics, title cards, and logo reveals.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
155 skills found
Automate Adobe After Effects tasks using the Model Context Protocol. Manage compositions, layers, keyframes, effects, and expressions for motion graphics, title cards, and logo reveals.
An automated memory middleware for AI agents, implementing a Retrieve-Respond-Save loop to maintain long-term persistent context across conversations.
Create and test AI-ready MCP tools for any web application. Inject code, automate browser interactions, and turn websites into intelligent agents.
Guide for integrating and managing custom Model Context Protocol (MCP) servers within the Cursor IDE environment.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.
Semantic Go code navigation and analysis tool using the Language Server Protocol (LSP) for accurate, high-performance project intelligence.
A guide for building high-quality MCP (Model Context Protocol) servers in Python or TypeScript to integrate external APIs and services into LLM workflows.
Proactive context window management for AI agents via intelligent token monitoring, snapshot creation, and selective state rehydration to maintain continuity during long sessions.
Maintenance patterns for the @youdotcom-oss/mcp STDIO bridge, focusing on transport lifecycle management, shutdown guards, and robust error handling.
Shared memory and collaboration layer for AI coding agents to track actions, manage sessions, detect conflicts, and preserve project context across tools.
A command-line tool to list, configure, authenticate, call, and inspect Model Context Protocol (MCP) servers via HTTP or stdio.
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.