AI MemoryCore is a universal AI memory architecture that helps create AI companions maintaining memory across conversations. It offers persistent memory, personal learning, time intelligence, simple setup, markdown database, session continuity, and self-maintaining features. The system uses markdown files as a database and includes core components like Master Memory, Identity Core, Relationship Memory, Current Session, Daily Diary, and Save Protocol. Users can set up, configure, activate, and use the AI for learning and growth through conversation. The tool supports basic commands, custom protocols, effective AI training, memory management, and customization tips. Common use cases include professional, educational, creative, personal, and technical tasks. Advanced features include auto-archive, session RAM, protocol system, self-update, and modular design. Available feature extensions cover time-based aware system, LRU project management system, memory consolidation system, and skill plugin system.

Tandem is a local-first, privacy-focused AI workspace that runs entirely on your machine. It is inspired by early AI coworking research previews, open source, and provider-agnostic. Tandem offers privacy-first operation, provider agnosticism, zero trust model, true cross-platform support, open-source licensing, modern stack, and developer superpowers for everyone. It provides folder-wide intelligence, multi-step automation, visual change review, complete undo, zero telemetry, provider freedom, secure design, cross-platform support, visual permissions, full undo, long-term memory, skills system, document text extraction, workspace Python venv, rich themes, execution planning, auto-updates, multiple specialized agent modes, multi-agent orchestration, project management, and various artifacts and outputs.

LLMos is an operating system designed for physical AI agents, providing a hybrid runtime environment where AI agents can perceive, reason, act on hardware, and evolve over time locally without cloud dependency. It allows natural language programming, dual-brain architecture for fast instinct and deep planner brains, markdown-as-code for defining agents and skills, and supports swarm intelligence and cognitive world models. The tool is built on a tech stack including Next.js, Electron, Python, and WebAssembly, and is structured around a dual-brain cognitive architecture, volume system, HAL for hardware abstraction, applet system for dynamic UI, and dreaming & evolution for robot improvement. The project is in Phase 1 (Foundation) and aims to move into Phase 2 (Dual-Brain & Local Intelligence), with contributions welcomed under the Apache 2.0 license by Evolving Agents Labs.

LAYRA is the world's first visual-native AI automation engine that sees documents like a human, preserves layout and graphical elements, and executes arbitrarily complex workflows with full Python control. It empowers users to build next-generation intelligent systems with no limits or compromises. Built for Enterprise-Grade deployment, LAYRA features a modern frontend, high-performance backend, decoupled service architecture, visual-native multimodal document understanding, and a powerful workflow engine.

AgriTech is an AI-powered smart agriculture platform designed to assist farmers with crop recommendations, yield prediction, plant disease detection, and community-driven collaboration—enabling sustainable and data-driven farming practices. It offers AI-driven decision support for modern agriculture, early-stage plant disease detection, crop yield forecasting using machine learning models, and a collaborative ecosystem for farmers and stakeholders. The platform includes features like crop recommendation, yield prediction, disease detection, an AI chatbot for platform guidance and agriculture support, a farmer community, and shopkeeper listings. AgriTech's AI chatbot provides comprehensive support for farmers with features like platform guidance, agriculture support, decision making, image analysis, and 24/7 support. The tech stack includes frontend technologies like HTML5, CSS3, JavaScript, backend technologies like Python (Flask) and optional Node.js, machine learning libraries like TensorFlow, Scikit-learn, OpenCV, and database & DevOps tools like MySQL, MongoDB, Firebase, Docker, and GitHub Actions.

evi-run is a powerful, production-ready multi-agent AI system built on Python using the OpenAI Agents SDK. It offers instant deployment, ultimate flexibility, built-in analytics, Telegram integration, and scalable architecture. The system features memory management, knowledge integration, task scheduling, multi-agent orchestration, custom agent creation, deep research, web intelligence, document processing, image generation, DEX analytics, and Solana token swap. It supports flexible usage modes like private, free, and pay mode, with upcoming features including NSFW mode, task scheduler, and automatic limit orders. The technology stack includes Python 3.11, OpenAI Agents SDK, Telegram Bot API, PostgreSQL, Redis, and Docker & Docker Compose for deployment.

Bifrost is a high-performance AI gateway that unifies access to multiple providers through a single OpenAI-compatible API. It offers features like automatic failover, load balancing, semantic caching, and enterprise-grade functionalities. Users can deploy Bifrost in seconds with zero configuration, benefiting from its core infrastructure, advanced features, enterprise and security capabilities, and developer experience. The repository structure is modular, allowing for maximum flexibility. Bifrost is designed for quick setup, easy configuration, and seamless integration with various AI models and tools.

BioAgents AgentKit is an advanced AI agent framework tailored for biological and scientific research. It offers powerful conversational AI capabilities with specialized knowledge in biology, life sciences, and scientific research methodologies. The framework includes state-of-the-art analysis agents, configurable research agents, and a variety of specialized agents for tasks such as file parsing, research planning, literature search, data analysis, hypothesis generation, research reflection, and user-facing responses. BioAgents also provides support for LLM libraries, multiple search backends for literature agents, and two backends for data analysis. The project structure includes backend source code, services for chat, job queue system, real-time notifications, and JWT authentication, as well as a frontend UI built with Preact.

Retrace is a local-first screen recording and search application for macOS, inspired by Rewind AI. It captures screen activity, extracts text via OCR, and makes everything searchable locally on-device. The project is in very early development, offering features like continuous screen capture, OCR text extraction, full-text search, timeline viewer, dashboard analytics, Rewind AI import, settings panel, global hotkeys, HEVC video encoding, search highlighting, privacy controls, and more. Built with a modular architecture, Retrace uses Swift 5.9+, SwiftUI, Vision framework, SQLite with FTS5, HEVC video encoding, CryptoKit for encryption, and more. Future releases will include features like audio transcription and semantic search. Retrace requires macOS 13.0+ (Apple Silicon required) and Xcode 15.0+ for building from source, with permissions for screen recording and accessibility. Contributions are welcome, and the project is licensed under the MIT License.

Claude Code Skills & Plugins Hub is a comprehensive marketplace for agent skills and plugins, offering 1537 production-ready agent skills and 270 total plugins. It provides a learning lab with guides, diagrams, and examples for building production agent workflows. The package manager CLI allows users to discover, install, and manage plugins from their terminal, with features like searching, listing, installing, updating, and validating plugins. The marketplace is not on GitHub Marketplace and does not support built-in monetization. It is community-driven, actively maintained, and focuses on quality over quantity, aiming to be the definitive resource for Claude Code plugins.

AionUi is a user interface library for building modern and responsive web applications. It provides a set of customizable components and styles to create visually appealing user interfaces. With AionUi, developers can easily design and implement interactive web interfaces that are both functional and aesthetically pleasing. The library is built using the latest web technologies and follows best practices for performance and accessibility. Whether you are working on a personal project or a professional application, AionUi can help you streamline the UI development process and deliver a seamless user experience.

Octocode is a methodology and platform that empowers AI assistants with the skills of a Senior Staff Engineer. It transforms how AI interacts with code by moving from 'guessing' based on training data to 'knowing' based on deep, evidence-based research. The ecosystem includes the Manifest for Research Driven Development, the MCP Server for code interaction, Agent Skills for extending AI capabilities, a CLI for managing agent capabilities, and comprehensive documentation covering installation, core concepts, tutorials, and reference materials.

sandboxed.sh is a self-hosted cloud orchestrator for AI coding agents that provides isolated Linux workspaces with Claude Code, OpenCode & Amp runtimes. It allows users to hand off entire development cycles, run multi-day operations unattended, and keep sensitive data local by analyzing data against scientific literature. The tool features dual runtime support, mission control for remote agent management, isolated workspaces, a git-backed library, MCP registry, and multi-platform support with a web dashboard and iOS app.

TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. It enables a data & learning flywheel for LLMs by unifying inference, observability, optimization, and experimentation. The platform includes a high-performance model gateway, structured schema-based inference, observability, experimentation, and data warehouse for analytics. TensorZero Recipes optimize prompts and models, and the platform supports experimentation features and GitOps orchestration for deployment.

Osaurus is a native, Apple Silicon-only local LLM server built on Apple's MLX for maximum performance on M‑series chips. It is a SwiftUI app + SwiftNIO server with OpenAI‑compatible and Ollama‑compatible endpoints. The tool supports native MLX text generation, model management, streaming and non‑streaming chat completions, OpenAI‑compatible function calling, real-time system resource monitoring, and path normalization for API compatibility. Osaurus is designed for macOS 15.5+ and Apple Silicon (M1 or newer) with Xcode 16.4+ required for building from source.

Claude Code Agents is an open-source AI agent system designed to enhance development workflows by providing specialized AI agents for orchestration, resilience engineering, and organizational memory. These agents offer specialized expertise across technologies, AI system with organizational memory, and an agent orchestration system. The system includes features such as engineering excellence by design, advanced orchestration system, Task Master integration, live MCP integrations, professional-grade workflows, and organizational intelligence. It is suitable for solo developers, small teams, enterprise teams, and open-source projects. The system requires a one-time bootstrap setup for each project to analyze the tech stack, select optimal agents, create configuration files, set up Task Master integration, and validate system readiness.

Trellis is an all-in-one AI framework and toolkit designed for Claude Code, Cursor, and iFlow. It offers features such as auto-injection of required specs and workflows, auto-updated spec library, parallel sessions for running multiple agents simultaneously, team sync for sharing specs, and session persistence. Trellis helps users educate their AI, work on multiple features in parallel, define custom workflows, and provides a structured project environment with workflow guides, spec library, personal journal, task management, and utilities. The tool aims to enhance code review, introduce skill packs, integrate with broader tools, improve session continuity, and visualize progress for each agent.

Unified AI Coding Assistant CLI for managing multiple AI agents like Claude Code, Google Gemini, OpenCode, and custom AI agents. Supports OpenAI, Azure OpenAI, AWS Bedrock, LiteLLM, Ollama, and Enterprise SSO. Features built-in LangGraph agent with file operations, command execution, and planning tools. Cross-platform support for Windows, Linux, and macOS. Ideal for developers seeking a powerful alternative to GitHub Copilot or Cursor.

oh-my-pi is an AI coding agent for the terminal, providing tools for interactive coding, AI-powered git commits, Python code execution, LSP integration, time-traveling streamed rules, interactive code review, task management, interactive questioning, custom TypeScript slash commands, universal config discovery, MCP & plugin system, web search & fetch, SSH tool, Cursor provider integration, multi-credential support, image generation, TUI overhaul, edit fuzzy matching, and more. It offers a modern terminal interface with smart session management, supports multiple AI providers, and includes various tools for coding, task management, code review, and interactive questioning.

AI MemoryCore is a universal AI memory architecture that helps create AI companions maintaining memory across conversations. It offers persistent memory, personal learning, time intelligence, simple setup, markdown database, session continuity, and self-maintaining features. The system uses markdown files as a database and includes core components like Master Memory, Identity Core, Relationship Memory, Current Session, Daily Diary, and Save Protocol. Users can set up, configure, activate, and use the AI for learning and growth through conversation. The tool supports basic commands, custom protocols, effective AI training, memory management, and customization tips. Common use cases include professional, educational, creative, personal, and technical tasks. Advanced features include auto-archive, session RAM, protocol system, self-update, and modular design. Available feature extensions cover time-based aware system, LRU project management system, memory consolidation system, and skill plugin system.

Claude Code Bridge (ccb) is a new multi-model collaboration tool that enables effective collaboration among multiple AI models in a split-pane CLI environment. It offers features like visual and controllable interface, persistent context maintenance, token savings, and native workflow integration. The tool allows users to unleash the full power of CLI by avoiding model bias, cognitive blind spots, and context limitations. It provides a new WYSIWYG solution for multi-model collaboration, making it easier to control and visualize multiple AI models simultaneously.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

Air-gapped Virtual Assistant / Personal Language Server

MetaGPT is a multi-agent framework that enables GPT to work in a software company, collaborating to tackle more complex tasks. It assigns different roles to GPTs to form a collaborative entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories, competitive analysis, requirements, data structures, APIs, documents, etc. Internally, MetaGPT includes product managers, architects, project managers, and engineers. It provides the entire process of a software company along with carefully orchestrated SOPs. MetaGPT's core philosophy is "Code = SOP(Team)", materializing SOP and applying it to teams composed of LLMs.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

Vanna is an open-source Python framework for SQL generation and related functionality. It uses Retrieval-Augmented Generation (RAG) to train a model on your data, which can then be used to ask questions and get back SQL queries. Vanna is designed to be portable across different LLMs and vector databases, and it supports any SQL database. It is also secure and private, as your database contents are never sent to the LLM or the vector database.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

Avalonia-Assistant is an open-source desktop intelligent assistant that aims to provide a user-friendly interactive experience based on the Avalonia UI framework and the integration of Semantic Kernel with OpenAI or other large LLM models. By utilizing Avalonia-Assistant, you can perform various desktop operations through text or voice commands, enhancing your productivity and daily office experience.

Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust. Each of Marvin's tools is simple and self-documenting, using AI to solve common but complex challenges like entity extraction, classification, and generating synthetic data. Each tool is independent and incrementally adoptable, so you can use them on their own or in combination with any other library. Marvin is also multi-modal, supporting both image and audio generation as well using images as inputs for extraction and classification. Marvin is for developers who care more about _using_ AI than _building_ AI, and we are focused on creating an exceptional developer experience. Marvin users should feel empowered to bring tightly-scoped "AI magic" into any traditional software project with just a few extra lines of code. Marvin aims to merge the best practices for building dependable, observable software with the best practices for building with generative AI into a single, easy-to-use library. It's a serious tool, but we hope you have fun with it. Marvin is open-source, free to use, and made with 💙 by the team at Prefect.

Activepieces is an open source replacement for Zapier, designed to be extensible through a type-safe pieces framework written in Typescript. It features a user-friendly Workflow Builder with support for Branches, Loops, and Drag and Drop. Activepieces integrates with Google Sheets, OpenAI, Discord, and RSS, along with 80+ other integrations. The list of supported integrations continues to grow rapidly, thanks to valuable contributions from the community. Activepieces is an open ecosystem; all piece source code is available in the repository, and they are versioned and published directly to npmjs.com upon contributions. If you cannot find a specific piece on the pieces roadmap, please submit a request by visiting the following link: Request Piece Alternatively, if you are a developer, you can quickly build your own piece using our TypeScript framework. For guidance, please refer to the following guide: Contributor's Guide