A JupyterLab extension supporting Claude Code, Copilot, Ollama, and OpenAI-compatible LLMs, with MCP, skills, plugins, and notebook agents.

MCP server for full Godot 4.x engine control: 157 tools for AI-driven game development (GDScript and C#/.NET). Tested with Godot 4.7.

Durable MCP control plane for long-running Codex Desktop tasks

Deterministic safety solutions for probabilistic AI agents

The Model Context Protocol (MCP) is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.

Fast, interruptible verification browser for AI coding agents: 35 ms checks, pixel diffs, live human hand-off

DeepSeek Harness plugin: give your agent a browser with a persistent identity - engine-level fingerprint spoofing, unlimited free local profiles, Android device emulation, passkeys that survive, and residential proxy egress.

The only browser automation that bypasses anti-bot systems. AI writes network hooks, clones UIs pixel-perfect via simple chat.

Cut AI context cost without trusting the compressor. Every reduction is reversible, byte-exact recoverable, and carries an auditable receipt. Local-first, works through proxy, MCP, SDK, or agent wrapper.

Hook-based token compressor for 5 AI CLI hosts (Claude Code, Copilot CLI, OpenCode, Gemini CLI, Codex CLI). Up to 95% bash compression, signature-mode for code reads, cross-call dedup, MCP server, self-teaching protocol. Zero runtime deps.

AI coding agent skills for KiCad electronics design. Works with Claude Code and OpenAI Codex. Analyze schematics, review PCB layouts, EMC pre-compliance, SPICE simulation, download datasheets, source components, and prep boards for fabrication.