Cursor Руководство установки
AI-редактор кода, часто используемый с developer MCP.
MCP Servers
AI-powered penetration testing MCP server
Linked API MCP server connects your LinkedIn account to AI assistants like Claude, Cursor, and VS Code.
Yet Another Frida MCP Server - Full-featured MCP server for Frida dynamic instrumentation
A CLI tool for managing MCP servers configurations for MCP clients.
Works transparently with , , , and any MCP-compatible agent. Also supports shell command governance and a language-agnostic HTTP API.
built by an autonomous agent · sibyl labs llc
Run it before Claude Code, Cursor, Windsurf, Cline, OpenCode, or another agent trusts new code, tools, prompts, or dependencies.
Local-first knowledge compiler for humans and agents. Inspired by Karpathy's vision. Plain markdown, CLI + MCP server.
Agent Skills
- 🤝 团队与**达成合作，Supervisor-Skills 正式作为**的核心科研技能完成部署，驱动「」与「」两大官方能力，将本项目沉淀的科研方法论带给亿级用户。 - 🚀 ：新增 paper-writer（证据门控的论文正文写作）、paper-polish（忠于原意的语言润色）、deep-research（综述级文献调研）三个技能；intro-drafter...
A Claude Code plugin that maintains FILETREE.md — a one-line description per file with content hashes for staleness detection.
Point it at an existing site and it finds the generic patterns, the missing states, and the sloppy code, then fixes them in place without rewriting your project.
DeepClause Typescript DML SDK and runtime
of cursor/plugins/pstack — kept in sync for standalone use. See also backnotprop/bro, referenced by the /bro skill below.
A股全栈数据工具包 · 十一层架构 · 54端点 · 19数据源 · 零鉴权 | Full-stack China A-share data toolkit for AI agents — 11 layers, 54 endpoints, 19 sources, zero-auth
Structured workflow packs for AI coding assistants, with built-in conversation memory, project memory, and learning-oriented collaboration patterns.
FTE+AI is an end-to-end program execution framework that guides R&D organizations through the complete journey of vendor replacement—from initial planning through successful cutover and optimization.
AI-native quantitative research framework
Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth.
Open-source Environment toolkit of claw-like agents, support task/harness generation and evaluation
Spec docs drift from code, or they bloat every PR. Skeeper picks neither.