Open Source AI Coding Tools - Page 9
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GSD 2
A powerful meta-prompting, context engineering
GSD 2 is a project focused on automating and streamlining development workflows through structured build systems and tooling. It aims to simplify the process of configuring, building, and deploying applications by providing predefined templates and automation scripts. The system is designed to reduce manual setup and improve consistency across development environments. It supports modular configurations, allowing users to adapt the build process to different project requirements. The project also emphasizes efficiency, enabling faster iteration and deployment cycles. It is particularly useful for teams looking to standardize their workflows and reduce friction in development pipelines. Overall, gsd-2 functions as a productivity tool for managing complex build and deployment processes. -
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GoDex
AI coding agent
GoDex is a developer-focused tool designed to enhance code exploration and understanding through AI-assisted workflows. It provides an interface that allows users to analyze codebases, generate insights, and interact with code using natural language queries. The system is built to improve productivity by reducing the time required to understand complex projects or unfamiliar code structures. It integrates with language models to provide contextual explanations, summaries, and suggestions. Godex emphasizes usability, offering a streamlined interface that fits into existing development environments. It also supports extensibility, allowing developers to adapt the tool to their specific workflows. Overall, Godex serves as an intelligent assistant for navigating and understanding codebases more efficiently. -
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Grida Assistant
Bring your Figma design & development pipeline to the next level
Bring your Figma design & development pipeline to the next level - with design-to-code, in-design-content-management, component management, and tools for faster design. -
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Grok of Death is a desktop coding assistant with GUI powered by the Grok API. Users supply their own API key — all billing is handled directly with xAI.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Groq AppGen
Project showcasing Llama 3.3 70B HTML codegen abilities
Groq AppGen is an interactive web application (built with Next.js and TypeScript) that uses Groq’s LLM API to generate or modify web application code based on natural-language prompts. Essentially, you tell the app what kind of web app or page you want (in plain English), and groq-appgen will produce HTML/JSX code scaffolding, layout, and optionally application logic accordingly. It supports iterative feedback: you can refine your prompt, adjust parameters or requirements, and have the app regenerate or update the code — facilitating rapid prototyping and experimentation. For developers or non-coding designers alike, groq-appgen lowers the barrier to building full web interfaces or small apps by leveraging LLM-driven code generation rather than writing boilerplate by hand. It integrates safety/content-checking via LlamaGuard to catch undesirable outputs, and includes session management, export/share functionality, and history tracking so you can iterate on designs or revert as needed. -
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Kimi K2.7 Code
Coding-focused Kimi model for long-horizon agent workflows
Kimi K2.7 Code is a coding-focused agentic model built on Kimi K2.6, designed for long-horizon software engineering, autonomous coding workflows, and complex tool-based execution. It improves end-to-end task completion across real-world programming scenarios while reducing thinking-token usage by about 30% compared with K2.6. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, 61 layers, 384 experts, a 256K-token context window, and a MoonViT vision encoder. The model supports image and video input, native INT4 quantization, interleaved thinking, and multi-step tool calling. It also forces preserve-thinking mode by default, retaining full reasoning context across multi-turn interactions to improve coding-agent consistency. K2.7 Code is recommended for use through Kimi Code CLI and can be deployed with vLLM, SGLang, or KTransformers. -
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Laravel Boost
Laravel-focused MCP server for augmenting AI powered local development
Boost is a Laravel-first toolkit that supercharges AI-assisted development by giving assistants structured, Laravel-aware context. At its core it runs as an MCP server that exposes a battery of Laravel-specific tools, so an AI agent can explore your app, inspect code and config, and take targeted actions instead of guessing. It ships opinionated, composable guidelines tuned for popular Laravel packages, which helps keep generated code idiomatic and consistent with framework norms. The package also curates a large body of vectorized Laravel ecosystem knowledge that’s scoped to what you’ve actually installed, improving retrieval precision and response quality. It’s designed to fit naturally into existing projects, supporting current Laravel releases and modern PHP runtimes with minimal setup. Rather than trying to replace your editor or framework, Boost acts like an intelligent layer that understands Laravel’s conventions and reduces the “explain my app to the AI” friction. -
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Leanstral
Open-source code agent designed for Lean 4
Leanstral is an open-weight large language model developed by Mistral AI and specifically designed as a code agent for the Lean 4 proof assistant, enabling advanced interaction with formal mathematics and program verification systems. The model is built to understand and generate Lean 4 code, which is used to express complex mathematical constructs as well as formal software specifications. By focusing on theorem proving and formal reasoning, Leanstral represents a specialized direction within large language models, targeting domains that require strict correctness and logical rigor rather than general conversational tasks. It leverages modern large-scale architectures, likely incorporating mixture-of-experts techniques, to balance efficiency and capability while handling structured symbolic reasoning tasks. The model can assist in writing proofs, exploring mathematical structures, and validating logical properties in code. -
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LongCat-2.0
Trillion-parameter MoE model for coding and million-token reasoning
LongCat-2.0 is Meituan’s flagship open-weight Mixture-of-Experts language model designed for frontier-scale coding, reasoning, and autonomous agent workflows. It features 1.6 trillion total parameters with approximately 48 billion activated per token, combining high capability with efficient sparse inference. The model was pretrained on more than 35 trillion tokens and trained entirely on a large-scale cluster of domestically developed AI accelerators, demonstrating stable frontier-scale training without rollback events. LongCat-2.0 introduces LongCat Sparse Attention and extensive 1M-context training, enabling native processing of million-token inputs for long-document analysis, repository-scale coding, and complex multi-step reasoning. Dedicated post-training further strengthens coding and agent performance, producing competitive benchmark results against leading proprietary models. -
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Loop Engineering
Practical patterns, starters & CLI tools for loop engineering with AI
Loop Engineering is a practical reference repository for designing loop-based workflows with AI coding agents. It focuses on replacing repeated manual prompting with systems that prompt, verify, schedule, and hand off work over time. The project is aimed at developers using tools such as Grok, Claude Code, Codex, Cursor, and other coding agents. It explains core building blocks such as scheduling, worktrees, skills, plugins, connectors, sub-agents, and persistent memory or state. The repository includes production loop patterns, quickstarts, starters, checklists, safety notes, and real-world stories. It also provides CLI tools such as loop-audit, loop-init, and loop-cost to scaffold, evaluate, and estimate agent loop workflows. -
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Luna Code Checker
An advanced web-based tool for checking JavaScript code using ESLint.
Luna Code Checker An advanced web-based tool for checking JavaScript code using ESLint. How to Use Clone the repository. Run npm install to install the dependencies. Run npm start to start the server. Open http://localhost:3000 in your web browser. Write or paste your JavaScript code in the textarea. Click the "Check Code" button to see linting results. Features Comprehensive syntax and style checking using ESLint. Detailed error messages including line numbers and descriptions. License This project is open source and available under the MIT License. -
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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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MathCode
A Frontier Mathematical Coding Agent
MathCode is a terminal-based AI coding assistant focused on mathematical formalization and theorem proving. It is designed to transform plain-language mathematical reasoning into verified Lean 4 code and formal proofs. The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive mathematical engineer than a one-shot text generator. MathCode also includes visualization-oriented tooling such as theorem graph generation for Obsidian knowledge workflows. Its main value is bridging natural-language mathematics with formal verification systems in a way that is more automated, inspectable, and iterative than traditional theorem-proving pipelines. -
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Mentat
Mentat - The AI Coding Assistant
Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. List the files you would like Mentat to read and edit as arguments. Mentat will add each of them to context, so be careful not to exceed the GPT-4 token context limit. -
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MiniMax Skills
Development skills for AI coding agents
MiniMax skills is a modular system designed to provide structured development capabilities for AI coding agents, enabling them to perform complex engineering tasks with guided workflows and domain-specific knowledge. It defines a set of reusable “skills” that encapsulate best practices, architectural patterns, and step-by-step processes for building applications across multiple platforms. These skills can be integrated into AI tools to improve the quality and consistency of generated code, particularly in areas such as frontend development, backend systems, mobile applications, and multimedia processing. The system supports a wide range of technologies and workflows, allowing developers to leverage AI assistance for both simple tasks and large-scale projects. It is designed to be extensible, enabling contributors to add new skills or enhance existing ones as development practices evolve. -
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MiniMax-M2
MiniMax-M2, a model built for Max coding & agentic workflows
MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real repositories and diverse programming languages. It is also optimized for multi-step agent tasks, planning and executing long toolchains that span shell commands, browsers, retrieval systems, and code runners. Benchmarks show that it achieves highly competitive scores on a wide range of intelligence and agent benchmarks, including SWE-Bench variants, Terminal-Bench, BrowseComp, GAIA, and several long-context reasoning suites. -
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Mods
AI on the command line
Mods is a command-line AI tool designed to make shell pipelines smarter. It lets users send text, command output, or file content to large language models and receive transformed results directly in the terminal. The project is useful for summarizing logs, rewriting text, formatting data, generating Markdown, producing JSON, and analyzing command output without leaving the shell. It works well with local LLMs and hosted providers, which gives users flexibility depending on privacy, cost, and performance needs. Mods fits naturally into Unix-style workflows because it can read from standard input and produce output that other commands can continue processing. Its main value is bringing practical AI assistance into everyday terminal automation. -
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Mysti
AI coding dream team of agents for VS Code
Mysti is a VS Code extension that provides a unified interface for AI coding assistants and agent workflows, with a strong emphasis on multi-agent collaboration. Instead of replacing the tools developers already use, it integrates with popular CLI-based coding assistants and routes work through a single, consistent UI inside the editor. The experience is organized around “personas” that change how the assistant approaches a task, such as architecture, debugging, security review, performance tuning, or refactoring, which helps structure the AI’s behavior for different goals. It also supports a brainstorm-style workflow where using more than one backend can produce competing solutions and then synthesize a best answer. Mysti is designed for speed and convenience with quick actions, toolbar persona switching, and a saved conversation history so work is not lost between sessions. -
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Omnara
Talk to Your AI Agents from Anywhere
Omnara is an open-source agent control platform that empowers developers to turn autonomous AI tools (e.g., Claude Code, Cursor, GitHub Copilot) into collaborative teammates by offering real-time dashboards, push notifications, and remote guidance across terminals, web, and mobile. Omnara transforms your AI agents (Claude Code, Codex CLI, n8n, and more) from silent workers into communicative teammates. Get real-time visibility into what your agents are doing, and respond to their questions instantly from a single dashboard on web and mobile. The primary way to use CLI coding agents (Claude Code, Codex CLI) with Omnara. -
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OpenReview
An open-source, self-hosted AI code review bot powered by Vercel
OpenReview is an open-source, self-hosted AI-powered code review system designed to automate and enhance the pull request review process using advanced language models. Built by Vercel Labs, it integrates directly with GitHub workflows, allowing developers to trigger intelligent code reviews by simply mentioning a bot in a pull request. The system operates in a sandboxed environment with access to the repository, enabling it to run linters, tests, and formatting tools as part of its review process. It provides detailed, line-by-line feedback and can suggest or even apply fixes directly to the codebase. OpenReview is designed for extensibility, supporting custom review skills that can be tailored to specific development needs or coding standards. Its architecture leverages Vercel’s infrastructure for scalable and reliable execution, ensuring that reviews can be resumed or retried if interrupted. -
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Ornith-1.0
Open reasoning model for agentic coding and tool workflows
Ornith-1.0 is a large open-source reasoning model from DeepReinforce, built for agentic coding, tool use, and complex software engineering workflows. It is part of the Ornith 1.0 family, which includes dense and MoE models post-trained on Gemma 4 and Qwen 3.5. The model focuses on coding-agent performance across benchmarks such as Terminal-Bench, SWE-Bench, NL2Repo, OpenClaw, and ClawEval. Its training uses a self-improving reinforcement learning framework that optimizes not only solution attempts but also the scaffolds that guide those attempts, helping the model discover better search paths and produce higher-quality solutions. Ornith-1.0-397B is a reasoning model by default, generating <think> blocks before final answers, and supports tool calling through OpenAI-compatible endpoints. It can be deployed with vLLM, SGLang, Transformers, Docker, and compatible quantized local apps, and is released under the MIT license. -
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Promptr
Promptr is a CLI tool that lets you use plain English to instruct GPT3
Promptr is a CLI tool that lets you use plain English to instruct OpenAI LLM models to make changes to your codebase. Changes are applied directly to the files that you reference from your prompt. -
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ProxyAI
The leading open-source AI copilot for JetBrains
ProxyAI is an open-source AI-powered coding assistant designed primarily for JetBrains IDEs, offering a highly customizable alternative to tools like GitHub Copilot while maintaining flexibility across multiple AI providers and deployment environments. It allows developers to connect to a wide range of language models, including cloud-based services and locally hosted models, enabling both online and fully offline workflows depending on user preferences. The platform emphasizes deep integration with the developer’s environment, providing context-aware assistance by referencing files, folders, Git history, and even external documentation during interactions. ProxyAI enhances productivity by enabling natural language-driven code editing, intelligent autocompletion, and automated generation of commit messages, all within the IDE interface. Its architecture supports extensibility and personalization, allowing users to tailor the assistant’s behavior through different personas. -
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Qwen of Death is a desktop coding assistant with GUI powered by the Qwen API. Users supply their own API key — all billing is handled directly with Openrouter.ai.
