Open Source BSD AI Coding Tools
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AI Coding Tools for BSD
Browse free open source AI Coding tools and projects for BSD below. Use the toggles on the left to filter open source AI Coding tools by OS, license, language, programming language, and project status.
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Claude Code
Claude Code is an agentic coding tool that lives in your terminal
Claude Code is an intelligent agentic coding assistant that lives in your terminal and understands your entire codebase. It helps developers code faster by executing routine tasks, explaining complex code snippets, and managing git workflows—all via natural language commands. Claude Code integrates seamlessly into your terminal, IDE, or GitHub by tagging @claude to interact with your code context. The tool is designed to simplify development by automating repetitive work and providing instant clarifications on code behavior. User feedback and usage data are collected responsibly, with strict privacy safeguards and limited retention, ensuring no feedback is used to train generative models. Claude Code is open and actively maintained with community-driven bug reporting and feature requests. Its natural language interface makes advanced coding workflows accessible without leaving your coding environment. -
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Bolt.new
Prompt, run, edit, and deploy full-stack web applications
Bolt.new is an AI-powered full-stack development platform created by StackBlitz that enables users to build, run, edit, and deploy complete web applications directly from the browser without requiring any local setup or traditional development environment. It operates as an intelligent coding agent where users describe what they want to build in natural language, and the system generates functional applications, including frontend, backend, and infrastructure components. The platform is built on StackBlitz’s WebContainers technology, which allows Node.js environments to run entirely in the browser, eliminating the need for installations while maintaining real development capabilities. Bolt.new is designed to significantly lower the barrier to entry for software creation, making it accessible not only to developers but also to product managers, designers, and non-technical users who want to quickly prototype or launch applications. -
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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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Grok CLI
An open-source AI agent that brings the power of Grok
Grok CLI is a command-line interface built around the Grok AI model that brings programmatic and conversational AI capabilities directly to developer terminals. It lets you run Grok queries from your shell, scripting environment, or automation workflows without switching to a browser, enabling utility in scripting, quick data exploration, code generation, and assistant-guided tasks directly where you write code. The CLI supports streaming responses, so outputs appear in real time as the Grok model generates them, making interactions feel responsive and fluid in terminal contexts. Grok CLI is designed to integrate with existing terminal habits—aliases, pipes, editors, and tooling—so you can combine AI assistance with native command-line workflows like grep, awk, and git. It also includes authentication support, configuration management, and caching options so frequent queries are efficient. -
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Graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
Graphify is a data visualization and transformation tool designed to convert structured or semi-structured data into graph-based representations, enabling better understanding of relationships and dependencies. It focuses on building visual models such as nodes and edges that represent entities and their connections, making complex datasets easier to interpret. The system likely supports dynamic updates, allowing graphs to evolve as data changes or new inputs are introduced. It is particularly useful in domains such as network analysis, knowledge graphs, and system architecture visualization. The architecture emphasizes flexibility, enabling users to customize how data is mapped and displayed. It may also include analytical features to explore patterns, clusters, or anomalies within the graph. Overall, Graphify serves as a bridge between raw data and visual insight. -
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Oh My OpenAgent
The best agent harness
Oh My OpenAgent is a large-scale, open-source agent orchestration framework that aims to provide a fully unified and extensible environment for AI-powered software development and automation. It builds on the idea that no single model is sufficient, instead enabling coordinated use of multiple models for reasoning, creativity, speed, and cost efficiency within a single workflow. The system is designed as a comprehensive agent harness where tasks are automatically decomposed, delegated, and executed across a network of specialized agents. It emphasizes openness and flexibility, allowing developers to integrate different providers and avoid dependency on any single ecosystem or vendor. The framework includes robust tooling for managing agent workflows, monitoring execution, and integrating external tools, making it suitable for complex, production-level use cases. It also fosters a strong community-driven development approach, with features evolving in real time. -
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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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M3E Canvas
Sketch Material 3 Expressive screens in the browser
M3E Canvas is a browser-based design tool for sketching Material 3 Expressive interfaces and turning them into prompts for AI coding tools. Users can drag buttons, cards, navigation bars, dialogs, fields, chips, images, and many other components onto a canvas. Screens can be linked together and tested as simple interactive flows before implementation. A Tidy function automatically aligns and groups nearby elements using Material-style spacing. Designs can be exported as PNG images or copied as prompts for tools such as Claude Code, Codex, Gemini CLI, and Cursor. Optional AI helpers can generate behavior notes and screen descriptions while keeping provider keys in the browser. Projects are stored locally and can also be shared through links. -
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Kimi Code CLI
Kimi Code CLI is your next CLI agent
Kimi CLI is a command-line AI agent that brings an intelligent software development assistant directly into your terminal, helping you with coding tasks, shell operations, and workflow automation without leaving your command prompt. It supports an interactive shell-like user interface where you can chat with the agent, request code edits, run shell commands, and receive contextual suggestions as you work, creating a seamless blend of AI-augmented development and traditional terminal usage. The tool includes integration with Zsh so that users can activate AI assistance via a hotkey while staying within their favorite shell environment, and it can serve as an Agent Client Protocol (ACP) server to bridge AI functionality into compatible IDEs and editors. Its support for well-established MCP tool configuration conventions lets developers connect the CLI to external tools and services during workflows, expanding its capabilities beyond simple queries into orchestrated development tasks. -
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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Kodus
AI code reviews, just like your senior dev would do
Kodus-AI is a framework for building, training, and deploying intelligent agents and models, especially focusing on practical AI workflows for businesses and automation. It provides a structured set of tools and abstractions that help teams design agent behaviors, orchestrate data pipelines, optimize inference, and integrate AI capabilities with applications or services. The platform often includes model management, scalable training workflows, and orchestration patterns that help teams move from research or prototypes to production-ready AI deployments. Through configurable pipelines and a focus on modularity, it supports experimentation while maintaining reproducibility and performance. Its tooling is typically designed to handle real-world imperatives like logging, monitoring, versioning, and hooking into operational infrastructure. -
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LazyCodex
The one and only agent harness for complex codebases
LazyCodex is an agent harness for using Codex on complex software projects. It is designed to add structure around AI coding sessions through memory, planning, execution, verification, skills, hooks, routing, and diagnostics. The project helps developers move beyond one-off prompts by giving the agent a more organized workflow inside a codebase. It supports project memory so context can persist across sessions and decisions do not need to be repeatedly reintroduced. LazyCodex also emphasizes verified completion, which means the workflow is built around checking whether tasks are actually finished rather than only generating code. Its main value is turning Codex into a more disciplined coding agent environment for larger and more demanding repositories. -
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Multica
The open-source managed agents platform
Multica is an open-source platform designed to manage and orchestrate AI coding agents as if they were real team members within a development workflow. It introduces a paradigm where agents can be assigned tasks, participate in discussions, and autonomously execute work while reporting progress and blockers in real time. The system integrates with multiple AI coding tools and provides a unified interface for managing tasks, compute environments, and agent execution pipelines. It includes both a web interface and a CLI that connects local or cloud-based runtimes to the platform, enabling flexible deployment and scaling. Multica emphasizes collaboration between humans and AI by allowing agents to operate alongside developers in shared workspaces. It also supports reusable skill accumulation, meaning that solutions generated by agents can be reused across projects to improve efficiency over time. -
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ClaudeBar
A macOS menu bar application that monitors AI coding assistant usage
ClaudeBar is a macOS menu bar utility that helps developers and power users monitor their AI coding assistant usage quotas from a lightweight system tray interface. Rather than constantly running CLI commands or navigating web dashboards, users can glance at their quota statistics for services like Claude, Codex, Gemini, GitHub Copilot, and Antigravity directly from the menu bar. The application provides real-time tracking of session, weekly, and model-specific usage percentages, using visual indicators such as color-coded progress bars to communicate when quotas are healthy, nearing limits, or depleted. It includes options to enable or disable monitoring for individual providers, supports multiple visual themes (including dark mode and a festive theme), and refreshes data at configurable intervals so users always have up-to-date information. -
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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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Happy Coder
Mobile and Web client for Codex and Claude Code, with realtime voice
Happy is an open-source, cross-platform mobile and web client designed to bring powerful AI coding agents such as Claude Code and Codex to your fingertips no matter where you are. At its core, Happy wraps existing AI coding tools with a unified interface, providing real-time voice interactions, encrypted communication, and seamless device switching between desktop and mobile. You can start a coding session locally through the Happy CLI or connect from a phone or browser, allowing developers to inspect, interact with, and guide the AI as it generates, tests, or explains code. The project includes components like a dedicated backend server for encrypted sync, a rich front-end experience across web and native apps, and support for push notifications when your coding agent encounters permission requests or errors. Happy prioritizes security with end-to-end encryption so your code and interactions remain private and auditable. -
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Markdown Viewer Agent Skills
Opinionated skills for AI coding agents to create stunning diagrams
Markdown Viewer Agent Skills is a repository that provides a collection of modular AI “skills” designed to extend the capabilities of agents or tools that operate on markdown-based workflows. These skills are typically structured as self-contained instruction sets that define how an AI should perform specific tasks, such as formatting, analysis, or content transformation. The project emphasizes simplicity and composability, allowing developers to integrate these skills into existing systems without requiring complex infrastructure. Each skill is designed to be reusable and adaptable, making it easy to customize behavior for different use cases. The repository aligns with the broader concept of agent skills, where capabilities are encapsulated into modular units that can be dynamically loaded and executed. It supports workflows that rely heavily on markdown as a primary medium for content and communication. -
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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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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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CoStrict
Strict AI coder for enterprises, quality first
CoStrict is an enterprise-focused, open-source AI coding assistant designed to standardize and elevate software development workflows through structured, high-quality automation. Unlike typical AI coding tools that prioritize speed over rigor, CoStrict introduces a “strict mode” methodology that enforces disciplined processes such as requirements analysis, architecture planning, task decomposition, and test generation before producing code. This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. The system integrates repository-wide analysis using retrieval-augmented generation, allowing it to understand large codebases and provide context-aware suggestions, reviews, and modifications. It also incorporates multi-agent or multi-expert verification strategies, ensuring that generated code is validated from multiple perspectives before being accepted. -
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CodexPro
Use ChatGPT Developer Mode as a local coding agent for your repo
CodexPro is a local MCP bridge that lets ChatGPT Developer Mode work inside a specific code repository. It starts a local server for the current workspace so ChatGPT can read files, search code, apply scoped edits, run guarded shell checks, and review changes. The project is designed around local control rather than hosting code or proxying model access through a third-party service. It supports setup, start, doctor, settings, handoff, and pro modes for different levels of agent involvement. Public access can be routed through options such as Cloudflare tunnels, ngrok, Tailscale Funnel, or local-only mode. CodexPro is useful for developers who want ChatGPT to act like a repo-aware coding assistant while keeping the actual workspace on their own machine. -
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Visual Studio Code client for Tabnine
Visual Studio Code client for Tabnine
This extension is for Tabnine’s Starter (free), Pro and Enterprise SaaS users only. Tabnine Enterprise users with the self-hosted setup should use the Tabnine Enterprise extension in the VSCode Marketplace. Tabnine is an AI code assistant that makes you a better developer. Tabnine will increase your development velocity with real-time code completions, chat, and code generation in all the most popular coding languages and IDEs. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, content assist, unit test generation or documentation generation, using Tabnine can massively impact your coding velocity, significantly cutting down your coding time. -
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Habit Tracker
Habit Tracker for the AI Coding Workshop
Habit Tracker is a personal habit-tracking web application designed to help users build and maintain daily habits through intuitive UI and analytics that visualize progress over time. It runs locally with a FastAPI backend (Python) and a React frontend, storing all data in a lightweight SQLite database so there’s no need for user accounts or cloud storage, which keeps habit data fully private and self-contained. The app provides streak tracking and completion rates for each habit, giving users feedback on consistency and motivation by showing how often habits are completed and where they may be lagging. A calendar view lets users see a monthly grid of their habit history with color-coded days to highlight patterns and encourage daily engagement. Habit-Tracker also supports planned absences so users can skip days without breaking their streaks, reducing frustration and keeping long-term habits on track. -
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Oh My OpenCode Slim
Slimmed, cleaned and fine-tuned oh-my-opencode fork
Oh My OpenCode Slim is a lightweight, optimized fork of the broader oh-my-opencode ecosystem, designed to deliver high-performance multi-agent coding workflows while significantly reducing token consumption and system overhead. It retains the core concept of orchestrating multiple specialized AI agents but streamlines their configuration, execution, and communication to make the system more efficient and practical for everyday use. The framework introduces a structured “pantheon” of agents, each with a defined role such as orchestration, exploration, and execution, allowing tasks to be automatically delegated and completed through coordinated workflows. It supports multiple AI providers and models, enabling users to mix and match capabilities depending on cost, speed, and performance requirements. -
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agentation
The visual feedback tool for agents
Agentation is a visual annotation and feedback tool designed to make interacting with AI coding agents more intuitive and precise by letting developers visually click on frontend elements in a browser and annotate them with context before sending structured feedback to an agent. Instead of describing UI elements in text — like “the blue button in the sidebar” — users click directly on elements to automatically capture selectors, positions, and contextual metadata that can be consumed by AI agents to locate exact code references. This approach dramatically improves clarity and reduces ambiguity when working with AI tools that generate or modify UI code, making the handoff between human design intent and AI execution much clearer. The package installs into a React app and shows a floating toolbar that lets you activate element selection and add notes during a development session, helping you capture precise targets for improved AI output. -
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agents-cli
CLI to turn coding assistants into expert at deploying AI agents
agents-cli is a command-line tool developed to simplify the creation, management, and execution of AI agents directly from the terminal. It provides developers with a structured interface for defining agent behavior, configuring tools, and running workflows. The tool integrates with agent frameworks and supports modular extensions for adding new capabilities. It emphasizes productivity by enabling rapid iteration and testing of agent logic without complex setup. agents-cli is designed to fit into modern developer workflows, particularly those that rely on automation and scripting. It allows users to orchestrate tasks, manage configurations, and monitor execution in a streamlined environment. Overall, it provides a developer-friendly entry point into agent-based systems.
