Open Source AI Coding Tools - Page 3
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AI Coding Tools
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Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Tabby
Self-hosted AI coding assistant
Tabby is an open-source, self-hosted AI coding assistant that provides code completion and suggestions within your preferred development environment. It enhances developer productivity by leveraging machine learning models to predict and generate code snippets. -
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9Router
Unlimited FREE AI coding. Connect Claude Code, Codex, Cursor, Cline
9Router is an AI routing and proxy platform designed to unify access to dozens of AI providers and coding assistants through a single local endpoint. The project allows developers to connect tools such as Claude Code, Cursor, Codex, Cline, Copilot, Gemini CLI, and other AI coding environments to multiple commercial, free, and fallback model providers without manually switching APIs. It includes smart routing logic that can automatically redirect requests between premium, low-cost, or free providers based on quotas, availability, or configuration rules. The system also offers a local dashboard for monitoring quotas, providers, models, and routing behavior in real time. 9router emphasizes flexibility and uninterrupted workflows by supporting failover mechanisms, provider pooling, and configuration-driven request management. Overall, it functions as a centralized AI gateway optimized for coding, experimentation, and multi-provider orchestration workflows. -
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Forge Code
AI enabled pair programmer for Claude, GPT, O Series, Grok, Deepseek
Forge is a modern, open-source tool that brings AI-powered code assistance directly into your terminal workflow, effectively turning your shell into a “pair programmer”, without ever leaving your development environment. Written in Rust (with a command-line interface), Forge integrates with your existing shell (bash, zsh, fish, etc.) or IDE-agnostic workflows, allowing you to interact with your codebase, command-line tools, and version control as usual, but with the added support of large language models (LLMs) to help with code generation, refactoring, bug fixing, code review, and even design advice. Rather than requiring a separate UI or web-based IDE, Forge respects the developer’s existing habits and setups, and keeps all operations local, ensuring your code doesn’t get sent to unknown external services — a strong point for privacy and security. It supports many model providers (e.g. GPT, Claude, Grok, and others) via API keys. -
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Qwen3-Coder
Qwen3-Coder is the code version of Qwen3
Qwen3-Coder is the latest and most powerful agentic code model developed by the Qwen team at Alibaba Cloud. Its flagship version, Qwen3-Coder-480B-A35B-Instruct, features a massive 480 billion-parameter Mixture-of-Experts architecture with 35 billion active parameters, delivering top-tier performance on coding and agentic tasks. This model sets new state-of-the-art benchmarks among open models for agentic coding, browser-use, and tool-use, matching performance comparable to leading models like Claude Sonnet. Qwen3-Coder supports an exceptionally long context window of 256,000 tokens, extendable to 1 million tokens using Yarn, enabling repository-scale code understanding and generation. It is capable of handling 358 programming languages, from common to niche, making it versatile for a wide range of development environments. The model integrates a specially designed function call format and supports popular platforms such as Qwen Code and CLINE for agentic coding workflows. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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System Prompts and Models of AI Tools
Full System Prompts, Internal Tools & AI Models
System Prompts and Models of AI Tools is a large open-source repository that collects and documents system prompts, internal tools, and model configurations used by popular AI platforms. It aggregates prompts from tools like Claude, Cursor, Devin AI, Perplexity, and many others to provide insight into how modern AI agents are structured and guided. The repository serves as a valuable resource for developers, researchers, and AI enthusiasts interested in understanding prompt engineering and agent behavior. By exposing these system-level instructions, it highlights how AI tools are designed to reason, act, and interact with users. It also emphasizes transparency and security awareness, especially around prompt leaks and vulnerabilities. Overall, it acts as a comprehensive knowledge base for studying and experimenting with real-world AI system prompts. -
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free-code
The free build of Claude Code
Free-code is an open-source platform aimed at providing accessible coding resources, tools, or templates that help developers learn, build, and share projects without barriers. It typically focuses on simplifying the development process by offering prebuilt components, example projects, or utilities that can be reused across different applications. The project is designed to encourage collaboration and knowledge sharing within the developer community, making it easier for beginners and experienced developers alike to access useful code snippets and frameworks. It may include a collection of curated resources that span multiple programming languages and use cases. Free-code emphasizes openness and accessibility, ensuring that users can freely explore, modify, and distribute the code. Its structure often supports modular usage, allowing developers to pick and choose what they need for their projects. -
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Aide
The open source AI-native IDE
Aide is an AI software engineering assistant that provides conversational code generation, analysis, and refactoring directly within your IDE or through a local web interface. Built to act as a full-stack collaborator, it understands multi-file projects, detects dependency relationships, and can generate consistent updates across files and frameworks. It supports multiple backends—including OpenAI, Anthropic, and open-source models—and can route requests based on task type or latency requirements. Aide stores context efficiently, caching embeddings of codebases to accelerate reasoning and maintain memory across sessions. Developers can query Aide for explanations, generate docstrings, fix bugs, or scaffold full modules, all while preserving project structure. With a modular architecture, Aide can run locally for privacy-sensitive work or connect to managed servers for collaborative environments. -
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Claw Code
AI agent harness for AI coding agents
Claw Code is an open-source AI agent harness project focused on building better tools for orchestrating and managing autonomous coding agents. It originated as a clean-room reimplementation inspired by the architecture of Claude Code, aiming to replicate core concepts without using proprietary code. The project provides a Python-based foundation for experimenting with agent workflows, tool integration, and task execution pipelines. It emphasizes harness engineering—how agents are structured, how they interact with tools, and how they maintain context during execution. The system is being actively expanded, with a Rust-based runtime in development to improve performance and memory safety. Overall, Claw Code serves as a research-driven platform for advancing agent-based software development systems. -
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Oh My codeX (OMX)
Your codex is not alone. Add hooks, agent teams, HUDs
Oh My codeX (OMX) is a multi-agent orchestration layer designed to extend the capabilities of OpenAI Codex CLI by introducing structured teamwork, automation, and advanced workflow management. It addresses limitations in the base Codex environment, such as the lack of hooks, agent coordination, and persistent execution, by layering a shell-based system that enables richer interaction patterns. The project transforms a single AI coding assistant into a coordinated system of specialized agents that can collaborate in parallel, improving both speed and reliability of development tasks. It leverages tools like tmux to manage multiple agent sessions simultaneously, enabling a “team mode” where different agents handle distinct responsibilities within a shared workflow. The system also introduces staged pipelines, allowing tasks to move through phases such as planning, execution, verification, and refinement in a structured manner. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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PyGPT
Open source personal AI Assistant for Linux, Windows and Mac
PyGPT is a desktop application that allows you to talk to OpenAI's LLM models such as GPT4 and GPT3 using your own computer and OpenAI API. It allows you to talk in chat mode and in completion mode, as well as generate images using DALL-E 2. PyGPT also adds access to the Internet for GPT via Google Custom Search API and Wikipedia API and includes voice synthesis using Microsoft Azure Text-to-Speech API. Moreover, the application has implemented context memory support, context storage, history of contexts, which can be restored at any time and e.g. continue the conversation from point in history, and also has a convenient and intuitive system of presets that allows you to quickly and pleasantly create and manage your prompts. Plugins support is also available. -
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VT Code
VT Code - semantic AI coding agent
VTCode is a terminal-based AI coding agent designed to provide semantic code understanding and interactive assistance directly within a command-line environment. It is implemented in Rust and focuses on performance, portability, and deep integration with developer workflows that rely on terminal tools. The system leverages syntax-aware parsing technologies such as tree-sitter and AST-based analysis to understand code structure rather than relying solely on raw text, which enables more accurate and context-aware suggestions. VTCode operates as an agent rather than a simple autocomplete tool, meaning it can interpret user intent, navigate codebases, and assist with multi-step tasks. It is highly configurable, allowing developers to define behavior, prompts, and workflows tailored to their projects. The tool is especially useful for developers who prefer lightweight, local-first environments but still want advanced AI assistance comparable to modern IDE-based tools. -
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AI Website Cloner Template
Clone any website with one command using AI coding agents
AI Website Cloner Template is a reusable project template that enables AI coding agents to reverse-engineer and recreate existing websites as modern, production-ready applications. It automates the process of analyzing a target website, extracting its design system, and rebuilding it using technologies such as Next.js, React, and Tailwind CSS. The system operates through a multi-stage pipeline that includes reconnaissance, component specification, parallel generation, and final assembly, ensuring high fidelity to the original design. It leverages AI agents to perform tasks such as capturing layouts, extracting styles, and generating code for each component. The template is designed for flexibility, allowing developers to customize the generated output or adapt it for different use cases such as migrations or learning. It also supports multiple AI coding environments, making it compatible with a wide range of development tools. -
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GitHub Copilot SDK
Multi-platform SDK for integrating GitHub Copilot Agent into apps
The GitHub Copilot SDK is a developer toolkit that enables creators to build custom AI-assisted experiences powered by Copilot models within their own applications, editors, and workflows. Instead of being limited to editors like VS Code, this SDK lets teams embed Copilot-style code suggestions, natural language assistance, and predictive completions anywhere they see fit—such as internal IDEs, browser extensions, documentation portals, or bespoke tools tailored to specific languages or frameworks. It provides a structured API surface for invoking the Copilot model in context with the surrounding user state, capturing document content, cursor position, and invocation triggers so suggestions are relevant and responsive. The SDK includes helpers for streaming completions, managing rate limits, handling authentication, and integrating with telemetry and analytics pipelines. -
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Kite
Primary Kite repo, private bits replaced with XXXXXXX
The main Kite repo (originally kiteco/kiteco) was intended for private use. It has been lightly adapted for publication here by replacing private information with XXXXXXX. As a result, many components here may not work out of the box. We used a variety of infrastructure, on a mix of cloud platforms, depending on what was most economical, though it was mostly on AWS. You should be able to develop, build, and test Kite entirely on your local machine. However, we do have cloud instances & VMs available for running larger jobs and for testing our cloud services. We bundle a lot of pre-computed datasets & machine learning models into the Kite app through the use of a custom filemap & encoding on top of go-bindata. The data, located in kite-go/client/datadeps, is kept in Git-LFS. -
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TraceRoot
Find the Root Cause in Your Code's Trace
TraceRoot.AI is an open source, AI-native observability and debugging platform designed to help engineering teams resolve production issues faster. It consolidates telemetry into a single correlated execution tree that provides causal context for failures. AI agents operate over this structured view to summarize issues, pinpoint likely root causes, and even suggest actionable fixes or draft GitHub issues and pull requests. It offers interactive trace exploration with zoomable log clusters, span and latency views, and code-linked insights. Lightweight SDKs for Python and TypeScript enable seamless instrumentation using OpenTelemetry, with support for both self-hosted and cloud deployment. Human-in-the-loop interaction is central: developers can guide reasoning by selecting relevant spans or logs, then verify agent reasoning through traceable context. -
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Alook
The collaboration layer for your AI workforce
Alook is an open-source, self-hosted platform for running local AI coding agents as a coordinated workforce. It lets users give agents defined roles, email addresses, task boards, calendars, and shared workflows so they can collaborate more like a real team. The platform connects local agents to external communication channels while keeping the actual agents and codebase running on the user’s own machine. It is designed for developers, solo founders, and teams that want multiple AI agents to handle development, operations, research, and routine work with clearer structure. Alook also emphasizes memory and traceability, so agents can remember past decisions, learn preferences, and keep a record of instructions and replies. Its main value is turning separate AI coding tools into an organized, always-on operating system for agent-based work. -
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CodeCursor
An extension for using Cursor in Visual Studio Code
Cursor is an AI code editor based on OpenAI GPT models. You can write, edit and chat about your code with it. At this time, Cursor is only provided as a dedicated app, and the team currently has no plans to develop extensions for other editors or IDEs. -
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DESIGN.md
A format specification for describing a visual identity
design.md is an open specification created by Google Labs that defines a standardized way to describe design systems for AI coding agents. It allows developers to encode visual identity elements such as colors, typography, spacing, and components in a structured format. The file combines machine-readable design tokens with human-readable explanations, enabling agents to generate consistent user interfaces aligned with a brand. By providing persistent design context, it eliminates the need to repeatedly describe styling requirements to AI tools. The format supports interoperability across platforms and tools, making it a potential standard for agent-driven UI generation. It also includes tooling for validation and exporting design tokens. The goal is to enable agents to produce accurate, on-brand designs automatically. -
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Dao Code
Open-source TypeScript terminal coding agent for DeepSeek-V4
Dao Code is an open-source terminal-native AI coding assistant built around DeepSeek V4 and a cost-conscious agent architecture. It reads code, writes code, runs commands, fixes bugs, and streams tool usage inside the terminal. The project emphasizes byte-stable prompts, prefix-cache reuse, and low-cost reflection or memory forks so longer coding sessions can remain affordable. It also includes cross-session memory that verifies saved facts against the current codebase instead of blindly trusting old context. Dao Code supports approval gates, slash commands, skills, MCP tools, hooks, custom subagents, permissions, crash recovery, shadow-git checkpoints, and autonomous long-task mode. It is aimed at developers who want a Claude Code-like workflow with stronger mainland China availability and DeepSeek-first economics. -
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Defang
Defang CLI and sample projects
Defang is a developer-centric platform that simplifies the process of developing, deploying, and debugging cloud applications. By leveraging AI-assisted tooling, Defang enables developers to swiftly transition from an idea to a deployed application on their preferred cloud provider. The platform supports multiple programming languages, including Go, JavaScript, and Python, allowing developers to start with sample projects or generate project outlines using natural language prompts. With a single command, Defang builds and deploys applications, handling configurations for computing, storage, load balancing, networking, logging, and security. The Defang Command Line Interface (CLI) facilitates interactions with the platform, offering installation options via shell scripts, Homebrew, Winget, Nix, or direct download. Developers can define services using compose.yaml files, which Defang utilizes to deploy applications to the cloud. -
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Every Code
Local AI coding agent CLI with multi-agent orchestration tools
Every Code (often referred to simply as Code) is a fast, local AI-powered coding agent designed to run directly in the terminal environment. It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with various AI providers, enabling users to route tasks across different models depending on their needs. Every Code also includes browser integration and automation capabilities, extending its usefulness beyond simple code generation into more complex development tasks. Customization is a key focus, with support for theming, configurable settings, and reasoning controls that allow developers to fine-tune how the agent behaves. -
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GSD Core
Meta-prompting, context engineering, spec-driven development system
GSD Core is the core framework behind Open GSD, a workflow system for AI-assisted software engineering. It is designed to keep agent-driven development organized by turning vague goals into structured research, plans, tasks, implementation phases, verification steps, and handoffs. The project focuses on cleaner context, verified work, and more honest project history when working with coding agents. It supports installation across several AI coding runtimes and offers profiles for different levels of workflow surface area. The system is especially useful for developers who use AI agents heavily and need more discipline around planning, execution, and review. It acts less like a single app and more like an execution layer for shipping software with agents. -
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Gajae-Code
Gajae Code MVP
Gajae-Code is an experimental coding-agent harness focused on structured planning, reviewable execution, and durable verification. It runs beside existing tools rather than hiding inside a specific agent runtime, so users can apply it to a chosen repository or isolated worktree. The workflow is built around clarifying requirements, planning before mutation, turning approved plans into goals, and tracking evidence until completion. It includes tmux-backed execution options for coordinating parallel workers when a task is large enough to benefit from them. Gajae-Code is useful for developers who want coding agents to behave less like single-prompt assistants and more like disciplined project collaborators. Its main value is giving AI coding work a clearer loop for interviews, plans, goals, execution checks, and evidence. -
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Google Antigravity SDK
Python library for building agents that leverages Google Antigravity
Google Antigravity SDK for Python is a Python library for building AI agents powered by Antigravity and Gemini. It provides a secure, scalable, and stateful infrastructure layer so developers can focus on agent behavior instead of manually implementing the full agent loop. The SDK includes a high-level Agent class for quick setup, as well as lower-level conversation and connection abstractions for more controlled workflows. It supports streaming responses, stateful sessions, custom Python tools, MCP server integration, hooks, policies, and event-driven triggers. The package relies on a compiled runtime binary distributed through platform-specific PyPI wheels, so installation from PyPI is required for normal use. Its main value is giving developers a structured Python framework for creating local, tool-using, multimodal, policy-controlled AI agents. -
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HolyClaude
AI coding workstation: Claude Code + web UI + 5 AI CLIs + headless
HolyClaude is a developer-focused toolkit designed to enhance and extend the capabilities of Claude Code environments by providing structured prompts, utilities, and workflow enhancements for AI-assisted coding. The project centers around improving how developers interact with AI agents, enabling more efficient code generation, debugging, and task execution through optimized prompt engineering. It includes predefined templates and interaction patterns that guide the AI toward producing more accurate and context-aware responses. HolyClaude emphasizes productivity by reducing friction in iterative development cycles, allowing users to refine outputs quickly without repeatedly crafting instructions from scratch. The toolkit is modular in nature, enabling developers to adapt it to different coding scenarios or integrate it into their existing workflows. It also reflects broader trends in AI-assisted development, where prompt design becomes a critical factor in output quality.
