Cursor Руководство установки
AI-редактор кода, часто используемый с developer MCP.
MCP Servers
Drop a .pcap file, ask questions in plain English — get answers backed by real tshark data.
Give Claude on the (claude.ai) and read/edit access to files and a whitelisted shell on your local machine, over HTTPS via Tailscale Funnel, gated by OAuth 2.1. No desktop app, no device install.
Intercept AI requests, track usage, inject MCP tools centrally
The . The historical and kept only for legacy/self-hosted workflows. New users should start with the extension-first path below.
Agent Skills
Skills based on the Layered Rails book and beyond
A template repository implementing Boris Cherny's productivity tips for AI-assisted coding with and .
A modular, stack-agnostic toolkit of security review skills for AI coding agents to autonomously find, reproduce, and patch vulnerabilities.
The practical guide to building AI agent harnesses — with real code examples you can copy and run.
MCP browser tools have a fundamental problem: . With Playwright MCP, every response includes the full accessibility tree plus console messages. After a few page queries, your context window is full.
The Architect A Claude Code meta-agent that designs complete software blueprints. Describe what you want to build. Get a complete blueprint. Let Claude Code build it for you. tododeia.
🧃 Token weight loss. Lean output compaction for terminal-heavy agent workflows. Works as a native CLI tool or as an extension to popular coding and agent frameworks.
Platform design skill pack: 450+ rules for Apple HIG, Material Design 3, and WCAG 2.2 across iOS, iPadOS, macOS, watchOS, visionOS, tvOS, Android, and Web.
Modern agents are not "a prompt + a tool." They are — with identity, memory, skills, tools, MCP integrations, guardrails, observability, evals, and a provider strategy.
A self-improving product system that reads daily reports, identifies the #1 actionable priority, and autonomously implements it.
An explainable, cautious AI-generated text risk analyzer for coding agents and local workflows.
This repository contains hands-on tutorials for learning LangChain, LangGraph, and Deep Agents, organized into two learning tracks: