mcp Tools

PI-Desktop is a local-first AI coding agent that runs on your desktop. It provides a structured, inspectable environment for developers to work with AI assistants, built on a modular architecture of Electron, Rust, and SQLite. It's designed for developers who want a powerful, extensible, and understandable AI coding workspace that respects boundaries and contracts.

Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.

Hyperframes is a tool that allows you to write HTML and render it as video. It solves the problem of programmatically creating video content without complex video editing software, making it ideal for developers, AI agents, and automated workflows that need to generate visual media on the fly.

Open Science is an AI research workbench that integrates coordinator and specialist agents, Python/R execution, and scientific data connectors into a single desktop workspace. It solves the problem of fragmented research tools by keeping questions, code, execution, and traceable artifacts together in persistent projects for reproducible workflows. It's designed for researchers and scientists on macOS, Windows, and Linux who need a model-agnostic, local-first environment for AI-assisted discovery.

Atlas is a native macOS editor built to manage the work around coding—research, planning, and knowledge—alongside the AI agent threads that turn them into commits. It solves the problem of fragmented workflows by providing a unified planning surface where teams of humans and multiple AI agents can collaborate efficiently. It's for developers and engineering teams who use AI coding assistants like Claude, Codex, and Gemini and want to coordinate their work in a single, local-first application.

Awesome MCP Servers is a comprehensive, searchable directory for Model Context Protocol (MCP) servers. It solves the problem of discovery and evaluation by providing a centralized hub where developers can find, filter, and compare thousands of servers by attributes like language, category, and quality. It's designed for AI developers, prompt engineers, and anyone building with MCP who needs to quickly find the right tools to connect to their AI applications.

OpenSEO is an open source alternative to tools like Semrush and Ahrefs, providing quality SEO data to prevent AI from giving generic advice. It solves the problem of disconnected SEO strategy by allowing you and your AI agents to collaborate on keyword research, competitor analysis, and content planning. It's built for SEO professionals and businesses who want tailored, actionable insights without the bloat and high cost of traditional platforms.

Hister is a self-hosted search engine that indexes the full content of the web pages you visit and the files you keep. It solves the problem of losing useful information by creating a private, searchable memory of your digital content, putting you back in control of your data. It's for privacy-conscious individuals, researchers, and anyone who wants to reliably find information they've previously encountered without relying on external services.

The Claude Code Plugins repository is the official, Anthropic-managed directory for high-quality plugins that extend the Claude Code platform. It solves the problem of fragmented, hard-to-share custom configurations by providing a centralized marketplace for developers to discover, install, and contribute plugins that add skills, agents, automation hooks, and MCP servers. This is primarily for developers and engineering teams using Claude Code who want to enhance their workflows with reusable, community-vetted extensions.

AI Engineering from Scratch is a comprehensive, open-source curriculum that provides the missing spine for AI education. It solves the problem of scattered, framework-first learning by having you implement every core algorithm—from backprop to transformers—using only math and code, before any libraries are introduced. It's designed for engineers and students who want deep, foundational understanding and the ability to build, debug, and ship AI systems with confidence.

n8n is a fair-code workflow automation platform that lets you visually build and control AI agents and business processes. It solves the problem of rigid, limited automation by combining a visual canvas with custom code, enabling limitless logic and seamless data movement between 400+ apps. It's built for technical teams like IT Ops, Sec Ops, and developers who need powerful, transparent, and self-hostable automation.

This is an open-source book titled 'Deep Understanding of AI Agent: Design Principles and Engineering Practice' by Li Bojie. It provides a systematic guide to the core concepts, design principles, and practical engineering techniques for creating effective AI agents. The repository contains the full book text, compiled PDFs, and chapter-by-chapter example code. It is designed for developers, engineers, and researchers who want to move beyond simple AI models and learn how to architect and implement sophisticated, autonomous agent systems.

This is an open-source library of 734 structured cybersecurity skills following the agentskills.io standard. It solves the problem of AI agents lacking domain-specific, actionable cybersecurity knowledge by providing pre-built, framework-mapped workflows. It's designed for developers and security professionals using AI coding assistants like Claude Code, GitHub Copilot, and Cursor to enhance their agents' security capabilities.

holaOS is an open-source, all-in-one workspace for AI agents. It solves the problem of fragmented AI tools by letting you run any agent (like Claude Code or Codex) across your entire digital environment—100+ integrations, apps, browser, and files—with shared memory for seamless context. It's built for developers and teams who want to centralize their AI workflows, offering built-in models or the flexibility to bring your own keys.

Macro is an open-source office suite that unifies email, chat, docs, tasks, CRM, and AI into a single workspace. It solves the problem of fragmented communication and data across dozens of apps by providing a shared, team-level memory built from all your work. It's built for modern teams who want to replace 7+ separate tools with one fast, secure, and intelligent system.

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

Code Review Graph is a local-first code intelligence graph for MCP and CLI. It builds a persistent, semantic map of your codebase, enabling AI coding assistants to understand context and dependencies without reading every file. This dramatically reduces context overhead in code reviews and large-repository workflows, making AI tools faster and more accurate. It's built for developers and teams working in complex codebases who want to leverage AI assistance without the performance and cost penalties of massive context windows.

ADR is a production-proven system for securing enterprise AI agents built on the Model Context Protocol (MCP). It solves the critical challenges of limited observability, insufficient robustness, and high detection costs by providing comprehensive telemetry, systematic red teaming, and scalable, two-tier detection. It is designed for large enterprises deploying AI agents at scale, as demonstrated by its deployment at Uber.

Agent-Reach is a command-line tool that gives AI agents the ability to read and search content from major platforms like Twitter, Reddit, YouTube, and GitHub. It solves the problem of AI agents being blind to real-time, public web data without requiring expensive or restrictive API integrations. It's built for developers and AI engineers who need to build agents with comprehensive, up-to-date internet awareness.

This MCP server connects AI coding agents directly to Chrome DevTools. It solves the problem of agents being unable to interact with or inspect live web pages, limiting their debugging and automation capabilities. It's for developers and teams building AI agents that need to analyze, test, or manipulate web content programmatically.

jcode is an open-source terminal coding agent written in Rust, designed as a harness to maximize the capabilities of AI models. It tackles the limitations of current AI benchmarks and agent systems by focusing on scaling test-time compute, parallelism, and memory for continual learning. It's built for developers and researchers who want a powerful, transparent, and efficient general-purpose dev tool for day-to-day work and advancing agent capabilities.