List of the Top AI Coding Assistants for Mac in 2025 - Page 3

Optimize the management of your source code context and develop powerful prompts for coding tasks using tools such as ChatGPT and Claude. With the innovative 16x Prompt feature, developers can efficiently manage source code context and streamline the execution of intricate tasks within their existing codebases. By inputting your own API key, you gain access to a variety of APIs, including those from OpenAI, Anthropic, Azure OpenAI, OpenRouter, and other third-party services that are compatible with the OpenAI API, like Ollama and OxyAPI. This utilization of APIs ensures that your code remains private and is not exposed to the training datasets of OpenAI or Anthropic. Furthermore, you can conduct comparisons of outputs from different LLM models, such as GPT-4o and Claude 3.5 Sonnet, side by side, allowing you to select the best model for your particular requirements. You also have the option to create and save your most effective prompts as task instructions or custom guidelines, applicable to various technology stacks such as Next.js, Python, and SQL. By incorporating a range of optimization settings into your prompts, you can achieve enhanced results while efficiently managing your source code context through organized workspaces that enable seamless navigation across multiple repositories and projects. This holistic strategy not only significantly enhances productivity but also empowers developers to work more effectively in their programming environments, fostering greater collaboration and innovation. As a result, developers can remain focused on high-level problem solving while the tools take care of the details.

Amazon Q stands out as the premier generative AI-assisted tool tailored for software development endeavors. It significantly improves the software development lifecycle by enabling agents to independently perform a range of tasks, including feature implementation, documentation, testing, code reviews, refactoring, and overseeing software updates. With the Amazon Q Developer, navigating the intricacies of the development process becomes remarkably easier. This tool possesses extensive knowledge of AWS, helping users optimize their cloud expenditures and resources while providing guidance on optimal architectural practices, analyzing operational issues, and addressing networking difficulties. Furthermore, Amazon Q Developer agents support the transformation of extensive enterprise workloads, facilitating the transition of .NET applications from Windows to Linux, modernizing mainframe applications, migrating and upgrading VMware workloads, and enhancing Java applications, all with the goal of streamlining processes and reducing costs. Its adaptability and wide-ranging capabilities render it an essential resource for developers aiming to boost the efficiency and productivity of their projects, ultimately leading to more successful outcomes.

Cline is an autonomous coding assistant seamlessly embedded in your IDE, capable of creating and modifying files, executing commands, browsing the internet, and more, all while ensuring you provide explicit consent at each step of the process. This tool is specifically designed to address complex software development issues in a systematic manner. With its ability to generate and alter files, navigate large codebases, access web resources, and execute terminal commands upon your approval, Cline offers a level of support that goes beyond basic code completion or technical help. In contrast to conventional AI scripts that function in isolated settings, this extension boasts an intuitive interface that necessitates your consent for every modification and command, thereby promoting a secure and user-friendly experience with autonomous AI. By utilizing such a system, developers are empowered to discover creative solutions while retaining complete oversight of their coding environment, thus enhancing productivity and innovation in their projects.

Defang is a platform tailored for developers that aims to simplify the entire process of developing, deploying, and debugging cloud applications. By leveraging AI-powered tools, Defang allows developers to transform their innovative ideas into fully functional applications hosted on their preferred cloud services in no time. Supporting multiple programming languages, including Go, JavaScript, and Python, the platform provides users with the ability to kickstart their projects by using example templates or generating outlines through natural language prompts. With a single command, Defang efficiently automates the building and deployment processes, seamlessly handling configurations for computing, storage, load balancing, networking, logging, and security. The user experience is further enhanced through the Defang Command Line Interface (CLI), which offers various installation options such as shell scripts, Homebrew, Winget, Nix, or direct downloads. By allowing developers to define their services using compose.yaml files, Defang streamlines the deployment of applications to the cloud. This innovative platform not only cuts down on the intricacies typically involved in cloud application development but also opens the door for developers of all experience levels to engage with cloud technology more effectively. Furthermore, its user-friendly approach ensures that even newcomers to cloud development can quickly grasp the necessary tools and processes to succeed.

Aide proactively proposes solutions and identifies any missing files in the given context. Our agent effectively resolves linter errors while incorporating relevant context through LSP tools. You are encouraged to implement AI-driven enhancements during your coding activities. We utilize lightweight checkpoints integrated with VS Code (bypassing git) to allow for seamless reversion to previous versions in case of agent mistakes. Our aim is to make Aide function like a genuine engineer, fostering a collaborative programming environment. You can engage in discussions about a problem by tagging the necessary file(s) and then proceed with modifications, or you might start with a few changes and assess their consequences. Drawing inspiration from the spotlight feature on MacOS, we have introduced a floating widget that is activated with CMD + K, enabling you to quickly request changes based on any selected text. Furthermore, we offer a tool called Sidecar, which coordinates the preparation and sending of prompts to LLMs while providing access to various editor features, thus enhancing the entire coding experience. This innovative strategy effectively merges human intuition with machine productivity, making the programming process smoother and more efficient. Ultimately, our mission is to refine this collaborative dynamic, ensuring that developers can focus on creativity while leveraging AI assistance seamlessly.

Trae is a groundbreaking AI-powered integrated development environment (IDE) designed to revolutionize the experience of developers by facilitating seamless cooperation between human programmers and artificial intelligence. This collaborative model ensures that each task is handled by the most suitable participant, leading to heightened productivity and efficiency across projects. By merging human intuition with AI capabilities, Trae equips developers to launch their products to market more promptly and effectively. Moreover, this partnership cultivates a space where both creativity and technical skills can thrive in unison, ultimately enhancing the development landscape. With Trae, the future of development is not just about speed, but also about fostering innovative solutions.

The SWE-agent is an advanced AI-powered system designed to automate a wide range of activities, such as managing GitHub issues, performing cybersecurity tasks like Capture The Flag (CTF) challenges, and solving programming problems. By leveraging cutting-edge language models such as GPT-4 or Claude, it functions within secured computing environments to carry out its duties autonomously, offering tailored solutions for both developers and cybersecurity professionals. This adaptable tool serves various purposes, from improving software repositories to identifying security vulnerabilities and executing targeted operations. Developed through a partnership between researchers from Princeton and Stanford University, the SWE-agent showcases the fusion of machine learning with practical problem-solving in the fields of software engineering and cybersecurity. Its groundbreaking capabilities signify a substantial leap forward in the automation of intricate workflows, ultimately enhancing productivity for experts in these industries. Furthermore, the SWE-agent sets a new standard for the future of AI-assisted development and security measures.

Devika stands out as a pioneering open-source AI software engineer that translates high-level directives into manageable tasks, collects relevant data, and generates code to fulfill designated objectives. Utilizing cutting-edge language models, reasoning methodologies, and browsing capabilities, Devika adeptly supports software development while tackling complex programming issues with minimal human intervention. This platform is designed to work with a wide array of programming languages and includes vital features like advanced AI planning, contextual keyword extraction, and real-time agent oversight. Aspiring to challenge proprietary AI alternatives, Devika serves as a bold, open-source option for developers in need of adaptive assistance for their projects. By aiming to enhance the coding experience, it ultimately strives to empower programmers and boost overall productivity, ensuring that innovation in software development remains accessible to all. Furthermore, its commitment to transparency and collaboration in development sets it apart in an increasingly competitive landscape.

Fynix operates as an advanced AI-powered platform designed to boost the efficiency of software development by offering intelligent coding assistance and agent-based code evaluations. This innovative tool integrates effortlessly with popular IDEs, including VS Code, and boasts features such as context-aware autocomplete, the ability to input natural language for code corrections and translations, and automatic visual representations of code flow. With its Code Assistant capability, Fynix empowers developers to write cleaner and more efficient code at a faster rate, while the upcoming Code Quality Agent aims to enhance bug detection and maintain coding standards. Supporting multiple programming languages and frameworks, along with compatibility with tools like Jira, Fynix emerges as a versatile solution that promotes better coding practices and encourages team collaboration. As developers continuously seek to refine their skills and produce high-quality code, Fynix has established itself as a vital partner in the evolving realm of software development, ensuring that teams can work more effectively together. Ultimately, the platform represents a significant advancement in the tools available to developers striving for excellence in their craft.

Codespell.ai is an innovative tool that harnesses the power of AI to enhance coding quality and boost developer productivity. One of its standout features, Design Studio, streamlines the project initiation process by automatically creating starter-kit codebases along with well-organized designs, making the development journey smoother and more efficient. Additionally, this tool empowers developers by reducing the time spent on repetitive tasks, allowing them to focus more on creative coding solutions.

CodeNext.ai serves as an advanced AI-powered coding assistant specifically designed for Xcode developers, providing features such as intuitive context-aware code completion and interactive chatting options. It boasts compatibility with a wide array of leading AI models, including OpenAI, Azure OpenAI, Google AI, Mistral, Anthropic, Deepseek, Ollama, and more, giving developers the flexibility to choose and transition between models based on their needs. This tool delivers intelligent, real-time code suggestions as users type, which greatly enhances productivity and coding efficiency. Furthermore, its chat feature allows developers to engage in natural language conversations for various tasks, including coding, debugging, refactoring, and executing different coding functions both inside and outside the codebase. CodeNext.ai also integrates custom chat plugins, enabling the execution of terminal commands and shortcuts directly from the chat interface, which significantly streamlines the development workflow. Ultimately, this cutting-edge assistant not only simplifies coding activities but also fosters improved collaboration among team members, making it an essential tool for modern software development. By leveraging these capabilities, developers can accelerate their projects and enhance their overall coding experience.

Codex CLI is an open-source local coding agent designed to work seamlessly with your command line interface. It leverages OpenAI’s powerful Codex models to assist developers with writing, editing, and understanding code faster and more accurately. By integrating Codex CLI into their workflows, developers can automate repetitive tasks, get real-time code suggestions, and troubleshoot coding issues directly from their terminal. This tool provides a hands-on approach to coding automation, empowering developers to increase their productivity without needing to leave their preferred environment. With Codex CLI, developers can streamline their coding process, debug code with ease, and accelerate development, making it an invaluable tool for enhancing efficiency and code quality.

Gemini CLI is a next-generation, open-source AI agent that integrates Google’s Gemini 2.5 Pro model directly into developers’ command line terminals, providing a transformative upgrade to coding workflows. Free for individual developers with generous usage limits, Gemini CLI supports 60 model requests per minute and up to 1,000 requests per day, while also offering paid licenses for larger scale and multi-agent use cases. The CLI empowers users to generate code, debug, research, and automate complex tasks using simple, natural language prompts without leaving the terminal. It features real-time grounding through Google Search to provide accurate external context, as well as support for Model Context Protocol (MCP) extensions and prompt customization to adapt AI responses to specific projects. Gemini CLI is fully open source under the Apache 2.0 license, allowing developers to inspect, improve, and contribute to the codebase. Integration with Google’s AI coding assistant, Gemini Code Assist, enables seamless AI support across VS Code and the CLI. Developers can automate tasks non-interactively by scripting Gemini CLI commands, embedding AI into continuous integration workflows. The project welcomes contributions and community collaboration on GitHub to enhance security, features, and usability. With Gemini CLI, developers gain an accessible, powerful, and extensible AI tool directly within their primary development environment. It redefines the command line as a personalized, intelligent assistant, streamlining development from coding to deployment.

Junie, the AI coding agent by JetBrains, revolutionizes the way developers interact with their code by embedding intelligent assistance directly into JetBrains IDEs like WebStorm, RubyMine, and GoLand. Designed to fit naturally into developers’ existing workflows, Junie helps tackle both small and ambitious coding tasks by providing tailored execution plans and automated code generation. It combines the power of AI with IDE capabilities to perform code inspections, syntax checks, and run tests automatically, maintaining code quality without manual intervention. Junie offers two distinct modes: one for executing code tasks and another for interactive querying and planning, allowing developers to seamlessly collaborate with the agent. Its ability to comprehend code relationships and project logic enables it to propose efficient solutions and reduce time spent on debugging. Developers from various fields, including game development and web design, have showcased impressive projects built entirely or partly with Junie’s assistance. The tool supports multi-file edits and integrates version control system (VCS) assistance, making complex refactoring easier and safer. JetBrains offers multiple pricing plans tailored to individuals and organizations, ranging from free tiers to premium AI Ultimate for intensive daily use. By handling repetitive coding chores, Junie frees developers to focus on the creative and strategic aspects of software development. Overall, Junie stands as a powerful AI companion transforming traditional coding into a smarter, more collaborative experience.

Kiro is a sophisticated integrated development environment driven by artificial intelligence, aimed at optimizing AI-enhanced programming by converting natural language commands into organized requirements, system designs, and detailed implementation tasks, all of which undergo rigorous testing. Specifically tailored for autonomous workflows, it boasts functionalities such as specification-driven development, multimodal interactions, and "agent hooks" that trigger background operations during specific events like file saving, in addition to an autopilot feature that manages lengthy scripts while keeping the user actively involved. By proficiently handling context, Kiro reduces redundancy and eases the incorporation of intricate features within large codebases. Its native integrations with MCP facilitate effortless connections to documentation, databases, and APIs, while users can guide the development process through visual tools like user interface designs or architectural schematics. Emphasizing enterprise-grade security and privacy, Kiro ensures secure deployment, and its compatibility with Claude Sonnet models, Open VSX plugins, and established VS Code setups provides a seamless and AI-enhanced user experience. Furthermore, the platform is designed for continuous growth, adapting to user input and technological advancements to uphold its leadership in the realm of software development tools. This ongoing evolution guarantees that Kiro remains relevant and effective in meeting the dynamic needs of modern programmers.

Elastic Copilot is an extension designed for VS Code that acts as an AI-powered programming assistant, leveraging the extensive context windows of advanced models to create code that is ready for production without any constraints. It integrates smoothly within the editor, providing users with a terminal to execute commands, install libraries, run tests, and manage system tasks without the need to leave the development environment. The file system capabilities of the extension allow users to create, alter, and organize files and directories while maintaining a thorough understanding of the project's architecture. Furthermore, the inclusion of an in-editor web browser enables immediate testing of web applications, offering quick feedback on any changes made to the user interface. Each action taken is carefully recorded in a development history, allowing users to reflect on their workflow, revert to earlier points, and monitor the project's progression over time. Elastic Copilot excels in its capacity to generate complex functions, troubleshoot bugs, and refactor existing code, effectively converting natural language inquiries into structured code solutions. This not only streamlines the overall development process but also significantly boosts productivity, creating a more effective coding atmosphere that encourages continuous improvement. Consequently, developers can focus more on innovative aspects of their projects rather than getting bogged down in routine tasks.

Qoder is an advanced coding platform tailored for authentic software development, elevating standard code completion by incorporating sophisticated context engineering along with intelligent AI agents that have an in-depth understanding of your project. It allows developers to delegate complex, asynchronous tasks using its Quest Mode, where agents work autonomously to deliver comprehensive results, while also enhancing functionality through Model Context Protocol (MCP) integrations that interface with various external tools and services. Moreover, Qoder’s Memory system records coding styles, project-specific insights, and reusable context to ensure outputs remain consistent and pertinent to the project throughout the development lifecycle. Developers also have the option to engage in chat for guidance or code suggestions, maintain a Repo Wiki for gathering knowledge, and manage AI behavior through Rules to keep AI-generated work secure and well-directed. This blend of context-aware automation, agent delegation, and customizable AI behavior not only empowers teams to think critically and code more efficiently but also nurtures an environment conducive to innovation and collaboration. By harnessing these capabilities, Qoder transforms the coding experience, making it more streamlined and closely aligned with the unique requirements of each individual project while promoting a culture of continuous improvement and learning.

Codacy serves as an automated tool for code reviews, utilizing static code analysis to pinpoint issues, which in turn enables engineering teams to conserve time and address technical debt effectively. By integrating effortlessly with existing workflows on various Git providers, as well as platforms like Slack and JIRA through Webhooks, Codacy ensures that teams receive timely notifications regarding security vulnerabilities, code coverage, duplicate code, and the complexity of code with each commit and pull request. Additionally, the tool offers advanced metrics that shed light on the overall health of projects, team performance, and other key indicators. With the Codacy Command Line Interface (CLI), teams can perform code analysis locally, allowing them to access results without having to navigate to their Git provider or the Codacy web application. Supporting over 30 programming languages, Codacy is available in both free and enterprise versions, whether in the cloud or self-hosted, making it a versatile solution for various development environments. For more information and to explore its features, visit https://www.codacy.com/. Furthermore, adopting Codacy can significantly streamline your development process and enhance collaboration among team members.

Visual Studio IntelliCode significantly improves the development experience by providing AI-enhanced assistance tailored to individual needs. By emphasizing the suggestions that are most likely to be relevant, it effectively streamlines the coding process. The recommendations are based on extensive data gathered from numerous open-source projects on GitHub, each with a minimum of 100 stars. When integrated with your current code, the completion suggestions are tailored to reflect best practices in coding. In addition to aiding in statement completion, IntelliCode offers signature assistance, presenting the most pertinent overload options in relation to the context. This tool not only delivers customized recommendations for your code but also simplifies the process of sharing insights among your team members. With the introduction of this preview feature, you can establish a team model that generates personalized suggestions for code beyond the open-source spectrum, which includes methods from your unique utility classes or specialized libraries. Moreover, by incorporating our build task into your development workflow, you can maintain up-to-date team completions that adapt to changes within the repository, ultimately fostering a more collaborative and efficient coding atmosphere. As a result, IntelliCode serves as an essential resource for developers seeking to enhance both their productivity and teamwork capabilities.

StarCoder and StarCoderBase are sophisticated Large Language Models crafted for coding tasks, built from freely available data sourced from GitHub, which includes an extensive array of over 80 programming languages, along with Git commits, GitHub issues, and Jupyter notebooks. Similarly to LLaMA, these models were developed with around 15 billion parameters trained on an astonishing 1 trillion tokens. Additionally, StarCoderBase was specifically optimized with 35 billion Python tokens, culminating in the evolution of what we now recognize as StarCoder. Our assessments revealed that StarCoderBase outperforms other open-source Code LLMs when evaluated against well-known programming benchmarks, matching or even exceeding the performance of proprietary models like OpenAI's code-cushman-001 and the original Codex, which was instrumental in the early development of GitHub Copilot. With a remarkable context length surpassing 8,000 tokens, the StarCoder models can manage more data than any other open LLM available, thus unlocking a plethora of possibilities for innovative applications. This adaptability is further showcased by our ability to engage with the StarCoder models through a series of interactive dialogues, effectively transforming them into versatile technical aides capable of assisting with a wide range of programming challenges. Furthermore, this interactive capability enhances user experience, making it easier for developers to obtain immediate support and insights on complex coding issues.

Code Llama is a sophisticated language model engineered to produce code from text prompts, setting itself apart as a premier choice among publicly available models for coding applications. This groundbreaking model not only enhances productivity for seasoned developers but also supports newcomers in tackling the complexities of learning programming. Its adaptability allows Code Llama to serve as both an effective productivity tool and a pedagogical resource, enabling programmers to develop more efficient and well-documented software. Furthermore, users can generate code alongside natural language explanations by inputting either format, which contributes to its flexibility for various programming tasks. Offered for free for both research and commercial use, Code Llama is based on the Llama 2 architecture and is available in three specific versions: the core Code Llama model, Code Llama - Python designed exclusively for Python development, and Code Llama - Instruct, which is fine-tuned to understand and execute natural language commands accurately. As a result, Code Llama stands out not just for its technical capabilities but also for its accessibility and relevance to diverse coding scenarios.

Experience unmatched privacy and security with the latest version of ChatGPT, which boasts an array of advanced features. 1. The model training process does not incorporate customer data or prompts. 2. Data is protected through robust encryption methods, utilizing AES-256 for storage and TLS 1.2 or higher during transmission. 3. Adherence to SOC 2 standards is maintained for optimal compliance. 4. A user-friendly admin console streamlines the management of multiple members efficiently. 5. Enhanced security measures, including Single Sign-On (SSO) and Domain Verification, are integrated into the platform. 6. An analytics dashboard offers valuable insights into user engagement and activity trends. 7. Users benefit from unrestricted, fast access to GPT-4, along with Advanced Data Analysis capabilities*. 8. With the ability to manage 32k token context windows, users can process significantly longer inputs while preserving context. 9. Easily shareable chat templates promote effective collaboration within teams. 10. This extensive range of features guarantees that your organization operates both efficiently and with a high level of security, fostering a productive working environment. 11. The commitment to user privacy and data protection remains at the forefront of this technology's development.

Participate in collaborative conversations about your codebase while your AI coding assistant seamlessly updates multiple files within your chosen IDE! By automatically incorporating all active files in your editor, the assistant can utilize up to 128,000 tokens in its context memory. The AI handles various coding tasks, enabling you to either approve the comprehensive multi-file patch, choose specific sections to modify, or request further changes as necessary. Codebuddy is equipped to thoroughly scan your entire repository and establish a vector database, which allows it to identify suitable files for your needs or offer insights into your codebase, particularly useful if you aren't fully acquainted with it. This AI coding assistant boasts a profound knowledge of your repository, empowering you to create new files or alter numerous existing ones with a single command. Moreover, Codebuddy will automatically format code as a unified patch (diff), thereby enhancing your coding journey with exceptional multi-file capabilities. As a result of these advancements, your coding workflow can become significantly more efficient, leading to a notable boost in your overall productivity and allowing you to focus more on creative problem-solving.

Enhance your prototyping speed, improve coding efficiency, and elevate your overall productivity directly from your desktop, accessible at your convenience. With the ability to read, write, and modify both new and existing code, you can execute terminal commands and analyze the output while employing natural language queries to explore your entire codebase. Moreover, you can search the web for up-to-date information and documentation, as well as extract useful data from various online sources. CodeCompanion not only automates code generation and command execution but also gives you more time to focus on higher-priority tasks. This adaptable application is capable of creating new applications from scratch or aiding in the enhancement of ongoing projects. You can work in tandem with AI or let it autonomously handle tasks, adjusting effortlessly to both new and existing projects. The application understands, modifies, and creates code in multiple programming languages, offering automatic coding support and optimization features. In addition, CodeCompanion is proficient in executing shell commands, simplifying numerous tasks such as project setup, file creation, code modifications, software installations, and deployments, while providing insights based on your entire codebase to help you stay concentrated on your main goals. By integrating CodeCompanion into your workflow, you not only revolutionize your productivity but also transform the way you approach software development, making AI your essential ally in the process. With its comprehensive capabilities, you can take full advantage of every aspect of software creation and maintenance.

GPT Pilot represents a groundbreaking open-source AI tool that acts as a full-fledged developer, capable of crafting complete applications with minimal human oversight. Unlike standard code completion tools, GPT Pilot goes beyond by not only generating entire features but also diagnosing issues, engaging in problem-solving discussions, and requesting code evaluations. This innovative solution aims to revolutionize AI-assisted software development by taking on up to 95% of the coding workload, leaving just 5% for human programmers to manage. Furthermore, it integrates effortlessly with environments like VS Code, promoting real-time teamwork between developers and the AI. By fostering this collaboration, GPT Pilot allows developers to concentrate on intricate tasks while the AI efficiently tackles routine coding hurdles, ultimately enhancing productivity and creativity in software development. The synergy created by this tool may pave the way for a new era in programming practices.