An Agent Skill for the DL experiment lifecycle: RUN (a GPU you own or rent) → VERIFY the number is real → DELIVER reproducible, single-source figures and tables.

Scrape JavaScript-heavy sites and extract structured data via reusable CSS schemas. Portable agent skill wrapping the Crawl4AI CLI and Python SDK.

Unified real-time search MCP server supporting general web search, vertical domain search, parallel batch search, and full-page URL content extraction.

A self-contained browser engine that fetches, renders, and extracts web content as Markdown, JSON, or screenshots — no Chromium, no API key, no setup.

Native draw.io skill with export helpers, SVG linting, and public docs for Codex and Claude Code workflows.

Solve the blank canvas problem. Prompt → 3 distinct designs → vary → export. A Claude Code skill inspired by the Variant design community.

The one and only agent harness for complex codebases. Project memory, planning, execution, and verified completion inside Codex.

Example implementation of MCP Streamable HTTP client/server in Python and TypeScript.

Token-efficient MCP server for tabular data retrieval. Index CSV/Excel files, query rows, aggregate — 99%+ token savings vs raw file reads.

Rust-native MCP server for Office document processing (Excel, Word, PowerPoint). Sub-millisecond, local-first, open source.

👩‍💻 MCP server to index external repositories

LLM exposed as a 9P filesystem

Durable single-Agent Harness for TypeScript: recoverable Threads, context continuity, explicit side effects, and a native TUI.

Code Execution Sandbox Platform Solution for Individuals and Small Teams with MCP

Smithers is an agentic workflow framework for defining workflows in simple TypeScript configuration files and executing them quickly, durably, and reliably

Execute commands interactively on remote Windows machines using the WinRM protocol (just faster)

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

A system monitoring tool that exposes system metrics via the Model Context Protocol (MCP). This tool allows LLMs to retrieve real-time system information through an MCP-compatible interface.

Agent skills for LandingAI's Agentic Document Extraction (ADE) — production-ready document AI for agentic coding assistants

A code repository indexing tool to supercharge your LLM experience.

Unified AI Development Framework - BMAD phases with Ralph execution loop

A MCP server for symbolic manipulation of mathematical expressions

Enable AI assistants to explore and query your Steampipe data!

🚀 Custom modes for Roo Code VS Code extension - Enhanced AI coding assistance configurations