Author, generate, validate and govern AI agent rules, skills, plugins and MCP configuration across 52 coding assistants. Review with verified model evidence, evaluate skills, lock and sign dependencies, and publish bundles. CLI, MCP server and Go API.

A fast CLI tool to sync AI agent configurations and MCP servers across Claude, Copilot, Cursor, and more using symbolic links.

AI-orchestration dotfiles for developers who want leverage. Parallelize agents, enforce principles, and self-heal your stack for 100x throughput. Built to version the AI era.

Security auditor for AI agent configurations. Scans Claude Code setups for vulnerabilities, misconfigs, and injection risks.

Linter for AI agent configurations. Validates SKILL.md, CLAUDE.md, hooks, MCP, and more.

Lets Claude and other MCP clients hand coding tasks to the Codex CLI as a sub-agent, running under the user's own Codex configuration so any configured model provider (OpenAI, DeepSeek, local models) does the work. Provides tools to start, poll, cancel and inspect jobs with compact change summaries, long-task handling, token-saving lean mode and clean process teardown.

Lets AI coding agents build, test, and lint Android projects with Gradle, control devices and emulators via adb, automate UI through screenshots and input injection, and use a live IDE bridge for refactoring, code inspection, and run configurations. Works with any MCP client over stdio or authenticated HTTP.

Enables agents to ingest local registry snapshots, detect removed or newly deprecated tools and schema-breaking changes, verify deprecation claims against hash-chained evidence, and generate migration diffs for agent configurations.

Network Sketcher is an AI-ready network design tool with Local MCP, Online, and Offline editions for creating network designs and exporting PowerPoint diagrams and Excel-based configuration data.

Enables MCP clients to query and diagnose machine-learning training runs through read-only tools for listing experiments, reading configurations and final metrics, comparing runs, sampling metric curves, and detecting training failures.

Enables AI agents to set up, launch, monitor, and manage LoRA training runs through the ai-toolkit web UI API, including datasets, captions, job configuration, checkpoints, logs, loss curves, and sample images.

This server provides a standardized interface for interacting with the NovelAI image generation API, enabling agents to build and execute complex image creation workflows. It supports various generation types, from text-to-image and inpainting to parameter configuration, while providing Anlas cost estimation and semantic tag search.

MCP configuration to connect AI agent to a Linux machine.