v0.1.5 · MIT
Say goodbye to copy-pasting and DSH Token anxiety. Let ChatGPT on the web connect directly to your local project, code on its own, and hand complex tasks to DSH for sustained execution.
v1.0.0 · MIT
One capabilities.yaml wires skills, tools, rules, sub-agents, MCP servers, and plugins into Cursor, Claude Code, Codex, Windsurf, GitHub Copilot, and 30+ other AI coding agents
— · GPL-3.0
基于 Claude Code 的长篇网文辅助创作系统,解决 AI 写作中的「遗忘」和「幻觉」问题,支持 200 万字量级 连载创作。
— · See LICENSE file in repository root
Audit a website with the squirrelscan CLI and fix the findings in code. Runs SEO, performance, security, technical, content, accessibility, and 15 other rule categories (260+ rules), returns an LLM-optimized report, then drives an iterative fix loop, mapping issues to source files, applying fixes, a
— · MIT
Turn code into clarity. Generate accurate technical docs and AI-ready context in minutes—perfectly structured for human teams and intelligent agents.
— · Apache-2.0
Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support
v9.2.6 · MIT
Tribunal Kit is the governance layer for AI coding agents that stops AI hallucinations and npm ghost packages before they hit disk. Works with Cursor, Windsurf, Claude Code, and Aider.
— · Apache-2.0
Give any AI agent the ability to code
— · Apache-2.0
Plugin for JADX to integrate MCP server
— · MIT
🧩 MCP Gateway - A lightweight gateway service that instantly transforms existing MCP Servers and APIs into MCP servers with zero code changes. Features Docker deployment and management UI, requiring no infrastructure modifications.
v1.18.6 · MIT
MCP server for Adobe Premiere Pro with 384 core AI video editing tools, a guarded After Effects MOGRT studio, and a capability-aware UXP bridge for supported Premiere workflows.
v0.1.6 · MIT
DSH plugin: per-model proxy routing (http/https/socks5) with a settings UI — e.g. opencode/muse-spark-1.2-contributor needs a proxy while sibling models stay direct
— · Apache-2.0
Give any AI agent the ability to code
— · FSL-1.1-MIT
Extension manager for AI coding agents — install skills, subagents, MCP servers, rules, hooks, knowledge, and packs across Claude Code, Codex, Cursor, Copilot, and more.
v4.6.12 · MIT
Turn any laptop, desktop, VM, or server into a secure AI-agent workspace via MCP. Let ChatGPT, Claude, Grok, Qwen and other MCP clients read and edit files, run commands, test code, inspect systems, and complete real-world tasks.
v4.1.17 · AGPL-3.0-or-later
Local-first agent memory with MCP and an agent-native CLI. Documented clients include Claude Code, Cursor, and Windsurf.
— · Apache-2.0
MCP server for JADX-AI Plugin
— · no license
Render videos from React/Remotion component code via inference.sh. Pass TSX code, get MP4. Supports all Remotion APIs: useCurrentFrame, useVideoConfig, spring, interpolate, AbsoluteFill, Sequence. Configurable resolution, FPS, duration, codec. Use for: programmatic video generation, animated graphic
— · no license
Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation
v2.5.1 · MIT
AWS MCP server: call any AWS API from AI assistants - SSO device-code re-login, Cloud Control API CRUD, CloudWatch logs and metrics
— · AGPL-3.0
Self-hosted AI agent harness in a single Go binary — writes, sandbox-tests and repairs its own tools, and lets Claude Code, Codex and any MCP client build and share them.
— · no license
Run MATLAB® using AI applications with the official MATLAB MCP Server from MathWorks®. This MCP server for MATLAB supports a wide range of coding agents like Claude Code® and Visual Studio® Code.
v0.15.0 · MIT
Prove that what already worked still works after an agent changed the code. Picture checks, guards for fixed bugs, a pre-release walkthrough, and known-good markers — as a CLI and as an MCP server.
— · MIT
Runtime evidence that helps agents trace, profile, and burn down hotspots in application and native code, GPU kernels, and inference stacks.