Github Top Repositories

⚡ InsForge/InsForge is making waves. Here's the full picture. 🔗 https://github.com/InsForge/InsForge 📝 InsForge is a Postgres-based backend with auth, storage, compute, hosting, and AI gateway. Built for coding agents. ────────────────────────────── InsForge is a backend development platform designed for AI-native developers, providing a semantic layer between AI coding agents and backend primitives. Its key features include authentication, database, storage, model gateway, edge functions, and compute. To get started, you can either use the cloud-hosted version at insforge.dev or self-host using Docker Compose. The platform is suitable for developers looking to build AI-powered applications, and its documentation and community support are available for those who need help. InsForge is licensed under the Apache License 2.0, making it a great choice for open-source projects. Star the repository to show your support and get notified about new releases - InsForge: where AI meets backend development. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🎯 LadybirdBrowser/ladybird landed on trending. Worth a proper look. 🔗 https://github.com/LadybirdBrowser/ladybird 📝 Truly independent web browser ────────────────────────────── Check out Ladybird, a revolutionary web browser built from the ground up with a novel engine based on web standards. It's currently in pre-alpha, so it's best suited for developers who want to get involved early on. Key features include a multi-process architecture for improved security and robustness, with each tab running in its own sandboxed renderer process. It also inherits a range of core library support components from SerenityOS, such as LibWeb, LibJS, and LibCrypto. To get started, you can build and run Ladybird on Linux, macOS, Windows (with WSL2), and other *Nixes by following the build instructions. You can find code-related documentation in the documentation folder. If you're interested in contributing, join the Discord server to participate in development discussions and check out the CONTRIBUTING.md file for guidelines. Ladybird is licensed under a 2-clause BSD license, making it a great open-source project to get involved with. One-liner takeaway: Ladybird is the future of browsing, and you can be a part of it. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

CollectPay | International Business Payments Collect'n'Pay Collect'n'Pay helps businesses manage international payment operations, supplier payouts and multi-currency workflows across global markets. Learn how companies can use product for cross-border business payments, account setup, payment routing and operational support. A practical solution for teams working with international partners, suppliers and contractors. Ad. 18+

🌟 LearningCircuit/local-deep-research caught my eye on GitHub Trending today. 🔗 https://github.com/LearningCircuit/local-deep-research 📝 ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encrypted. ────────────────────────────── Local Deep Research is an AI-powered research assistant that allows you to control your data and research process. It uses multiple LLMs and search engines to perform deep, agentic research with proper citations. You can run it locally for privacy, build your own searchable knowledge base, and own your data. Key Features: - Performs deep, agentic research using multiple LLMs and search engines - Allows you to build your own searchable knowledge base - Runs locally for privacy, with no telemetry, analytics, or tracking - Uses SQLCipher encryption to protect your data Usage: You can install Local Deep Research using Docker, Docker Compose, or pip install. It works on Windows, macOS, and Linux. Technical Highlights: - Uses LangGraph Agent Strategy for autonomous agentic research - Supports 20+ research strategies for quick facts, deep analysis, or academic research - Includes SQLCipher encryption for secure data storage Audience: Local Deep Research is designed for individuals who want to take control of their research process and data. It's suitable for researchers, students, and anyone who wants to perform deep, agentic research while maintaining their privacy. In short, Local Deep Research is a powerful tool that puts you in control of your research and data - take back your research, take back your data. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: docusealco/docuseal — let's break it down. 🔗 https://github.com/docusealco/docuseal 📝 Open source DocuSign alternative. Create, fill, and sign digital documents ✍️ ────────────────────────────── DocuSeal is an open source platform for secure and efficient digital document signing and processing. It allows you to create PDF forms that can be filled and signed online on any device with a mobile-optimized web tool. Key features include a WYSIWYG form builder, 12 field types, automated emails, and files storage on disk or cloud services. The platform is easy to deploy in minutes and offers a live demo to try it out. It also has a range of pro features, including company logo and white-label, user roles, and automated reminders. For technical users, DocuSeal provides an API and webhooks for integrations, as well as support for Docker and Docker Compose. Overall, DocuSeal is ideal for businesses looking to integrate seamless document signing into their web or mobile apps. With its expertise and technologies, DocuSeal can help reduce the cost of developing and processing electronic documents while ensuring security and compliance. In short, DocuSeal is the perfect solution for anyone looking to streamline their document signing process - sign up now and start signing! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet PriorLabs/TabPFN: a gem from today's GitHub trending list. 🔗 https://github.com/PriorLabs/TabPFN 📝 ⚡ TabPFN: Foundation Model for Tabular Data ⚡ ────────────────────────────── Introduction to TabPFN: TabPFN is a powerful, PyTorch-based implementation of the TabPFN model, designed for fast and local inference with CUDA support. It's ideal for classification and regression tasks on tabular data. The tabpfn library provides an easy-to-use interface for creating and training TabPFN models. You can install it via pip: pip install tabpfn. To get started, use the default TabPFN-2.6 model with the following code:

from tabpfn import TabPFNClassifier, TabPFNRegressor

clf = TabPFNClassifier()
clf.fit(X_train, y_train)  
predictions = clf.predict(X_test)

reg = TabPFNRegressor()
reg.fit(X_train, y_train)  
predictions = reg.predict(X_test)

Key Features and Tips: - For optimal performance, use a GPU (even older ones with ~8GB VRAM work well). - Batch prediction mode is recommended, as each predict call recomputes the training set. - Avoid data preprocessing when feeding data to the model. Technical Highlights: TabPFN is part of a larger ecosystem, including the TabPFN Client for cloud-based inference and TabPFN Extensions for advanced utilities and features. Audience: This library is suitable for data scientists and machine learning engineers working with tabular data. In summary, TabPFN is a powerful tool for tabular data modeling - give it a try and experience the difference for yourself. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 addyosmani/agent-skills just hit the trending charts — here's why it matters. 🔗 https://github.com/addyosmani/agent-skills 📝 Production-grade engineering skills for AI coding agents. ────────────────────────────── The agent-skills repository provides a set of production-grade engineering skills for AI coding agents. These skills encode workflows, quality gates, and best practices that senior engineers use when building software. The repository includes 7 slash commands that map to the development lifecycle, activating the right skills automatically. The skills can be used with various tools such as Claude Code, Cursor, Gemini CLI, Windsurf, OpenCode, and GitHub Copilot. The repository also includes 20 skills that cover different aspects of software development, from defining and planning to building, verifying, and shipping. The skills are designed to be process-oriented, with a focus on workflows and step-by-step instructions rather than reference documentation. They also include anti-rationalization tables to help agents overcome common excuses for skipping steps. The key takeaway is: equip your AI coding agents with human-like skills to streamline your development workflow. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

💡 msitarzewski/agency-agents just hit the trending charts — here's why it matters. ⭐ 94002 · 🍴 15463 · 🐚 Shell · 🔥 +1,218 today 🔗 https://github.com/msitarzewski/agency-agents 📝 A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables. ────────────────────────────── 🎯 What it does The Agency is a collection of AI agent personalities, each with deep expertise, unique voice, and measurable outcomes, to transform workflows and deliver specialized services. ⚡ Why it's blowing up This repository is gaining massive attention due to its innovative approach to providing a complete AI agency at your fingertips, offering a wide range of specialized agents that can be easily integrated with various tools, making it a game-changer for businesses and individuals looking to streamline their workflows. 🛠 Key features - Specialized AI agents for various domains, including engineering, design, paid media, and sales - Unique personalities, communication styles, and approaches for each agent - Production-ready workflows and success metrics for measurable outcomes - Easy integration with tools like Claude Code, GitHub Copilot, and more 🚀 Quick start To get started, you can install all agents to your Claude Code directory using the ./scripts/install.sh --tool claude-code command, and then activate any agent in your Claude Code sessions. 👥 Who should care Businesses, entrepreneurs, and individuals looking to streamline their workflows, improve productivity, and gain a competitive edge through specialized AI services. 💬 Verdict The Agency is a revolutionary repository that provides a comprehensive AI solution, offering a wide range of specialized agents that can be easily integrated with various tools, making it a must-try for anyone looking to transform their workflow and achieve measurable outcomes. ────────────────────────────── 📅 May 06, 2026 · ⭐ 94002 | 🧠 @GithubRe

🐍 A Python project is trending: cocoindex-io/cocoindex — let's see what the fuss is about. ⭐ 8520 · 🍴 632 · 🐍 Python · 🔥 +438 today 🔗 https://github.com/cocoindex-io/cocoindex 📝 Incremental engine for long horizon agents 🌟 Star if you like it! #agentic-data-framework #ai #ai-agents #change-data-capture #codebase-intelligence #context-engineering ────────────────────────────── 1. 🎯 What it does — CocoIndex provides an incremental indexing framework for AI agents and LLM apps, keeping context fresh with minimal processing. 2. ⚡ Why it's blowing up — With the rapid growth of AI and LLM applications, CocoIndex is becoming essential for ensuring agents have access to up-to-date and relevant context, making it a crucial component in the development of intelligent systems. 3. 🛠 Key features — * Incremental processing * Any scale support * Declarative syntax * Live indexing * Vector search support 4. 🚀 Quick start — Install with pip install -U cocoindex and declare your data sources and targets to get started. 5. 👥 Who should care — Data engineers, AI and LLM app developers, and anyone working with intelligent systems that require fresh and relevant context. 6. 💬 Verdict — CocoIndex is revolutionizing the way AI agents and LLM apps interact with data, providing a crucial framework for ensuring context is always up-to-date and relevant. ────────────────────────────── 📅 May 06, 2026 · ⭐ 8520 | 🧠 @GithubRe

🎯 ruvnet/ruflo landed on trending. Worth a proper look. 🔗 https://github.com/ruvnet/ruflo 📝 🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, self-learning swarm intelligence, RAG integration, and native Claude Code / Codex Integration ────────────────────────────── Ruflo is a multi-agent AI orchestration platform for Claude Code. It enables 100+ specialized AI agents to collaborate across machines, teams, and trust boundaries. With Ruflo, agents self-organize into swarms, learn from every task, and remember across sessions. The platform provides a federated comms layer, self-learning capabilities, and vector memory. To get started, users can choose between two installation paths: the Claude Code Plugin for a lightweight setup or the CLI install for the full Ruflo loop. The CLI install provides a comprehensive setup with 98 agents, 60+ commands, and 30 skills. Ruflo's key features include swarm coordination, self-learning, and plugin marketplace with 32 native plugins. It also supports multi-provider models, including Claude, GPT, and Cohere, with smart routing. For security, Ruflo offers AIDefence, input validation, and CVE remediation. Ruflo is suitable for developers, researchers, and organizations looking to leverage AI orchestration for coding, testing, security, and documentation. The platform is designed to be extensible, with a wasm plugin for running sandboxed WebAssembly agents. Takeaway: Ruflo revolutionizes AI collaboration by providing a seamless, self-learning, and secure platform for multi-agent orchestration, making it an ultimate tool for anyone looking to harness the power of AI. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet mksglu/context-mode: a gem from today's GitHub trending list. 🔗 https://github.com/mksglu/context-mode 📝 Context window optimization for AI coding agents. Sandboxes tool output, 98% reduction. 14 platforms ────────────────────────────── Context Mode is a solution to the problem of context overload in tools like Playwright and GitHub. It's an MCP server that solves four key issues: context saving, session continuity, think in code, and output compression. With Context Mode, tools keep raw data out of the context window, reducing context size by up to 98%. It also tracks file edits, git operations, and other events, allowing the model to pick up where it left off. The ctx_execute function runs scripts that replace multiple tool calls, saving context. For example:

ctx_execute("javascript", `
  const files = fs.readdirSync('src').filter(f => f.endsWith('.ts'));
  files.forEach(f => console.log(f + ': ' + fs.readFileSync('src/'+f,'utf8').split('\\n').length + ' lines'));
`);

This approach reduces output tokens by ~65-75% while maintaining technical accuracy. Installation varies by platform, with options for Claude Code, Gemini CLI, and VS Code Copilot. The demo showcases Context Mode's capabilities. The takeaway: Context Mode is the key to unlocking efficient context management, and it's a game-changer for anyone working with MCP tools. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🚀 Meet bwya77/vscode-dark-islands: a gem from today's GitHub trending list. 🔗 https://github.com/bwya77/vscode-dark-islands 📝 VSCode theme based off the easemate IDE and Jetbrains islands theme ────────────────────────────── Could not generate summary at this time. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🌟 Hmbown/DeepSeek-TUI caught my eye on GitHub Trending today. 🔗 https://github.com/Hmbown/DeepSeek-TUI 📝 Coding agent for DeepSeek models that runs in your terminal ────────────────────────────── Could not generate summary at this time. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

🔥 docusealco/docuseal is trending — and it deserves your attention. 🔗 https://github.com/docusealco/docuseal 📝 Open source DocuSign alternative. Create, fill, and sign digital documents ✍️ ────────────────────────────── Could not generate summary at this time. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe