Open-source Amazon Q Developer alternatives

Gemini CLI is Google's open-source terminal agent for working with Gemini models from the command line. It offers a lightweight path from a prompt on the command line to the model, and it is designed for developers who spend their day in a shell. The project is written in TypeScript and licensed under Apache-2.0.

Built-in tools cover Google Search grounding, file operations, shell commands and web fetching, and further integrations can be added through the Model Context Protocol (MCP). The project highlights access to Gemini models with a large context window, and a free tier when you sign in with a personal Google account.

You can run it instantly with npx or install it globally with npm, Homebrew, MacPorts or Anaconda. It has preview, stable and nightly release channels published on a regular schedule. It suits developers who want an AI assistant for code and shell tasks without leaving the terminal.

OpenHands is an open-source project for AI-driven software development. Its current README centers on Agent Canvas, a self-hosted developer control center for starting conversations with coding agents and automating everyday engineering tasks. It is written mainly in TypeScript and released under the MIT license.

By default Agent Canvas uses the open-source OpenHands agent, but it can also drive third-party agents such as Claude Code, Codex and Gemini, or any ACP-compatible agent. It runs locally by default and can connect to several agent backends, including Docker containers, virtual machines and company infrastructure, so agents can be moved between local, remote and cloud setups without interrupting your work.

Automations can be triggered on a timetable or by incoming webhook events and connect with tools such as Slack, GitHub, Linear and Notion, for example publishing reports to Slack or breaking GitHub issues into tasks. Agents can optionally run on OpenHands Cloud or OpenHands Enterprise. It suits engineering teams that want to coordinate several coding agents from one self-managed place.

Continue is an open-source coding agent that was offered as a command-line tool, a VS Code extension and a JetBrains plugin. It is written in TypeScript and released under the Apache-2.0 license. According to the README, the project's GitHub repository has stopped receiving active maintenance and is now read-only, so new features and fixes should not be expected from it.

The team shipped a final 2.0.0 release for the VS Code extension, the CLI and the JetBrains plugin. That release removed anonymous telemetry and authentication, and fixed a batch of bugs. The maintainers recommend the CLI over the JetBrains plugin, and they point to the documentation for configuration and customization. The project describes the codebase as a foundation that others can build on, which makes it relevant as reference code more than as an actively developed product.

Kilo Code is an AI coding agent that you can use in VS Code, in JetBrains IDEs or from the CLI. It is open source under the MIT license and written in TypeScript. According to the README, you can pick from more than 500 models and switch between them in the middle of a task, and you pay the model provider's rate with no markup. No API keys are needed to start.

Besides the local extensions, a Cloud Agent runs Kilo from the web without a local machine, and automated AI code reviews can be set up for pull requests. The CLI is started with the kilo command in a project directory and can be installed from release binaries for Windows, macOS on Apple Silicon and Intel, and Linux on x64 and ARM, with variants for older CPUs and Alpine-style images. The repository started in 2025 and its README is translated into many languages.

Aider is AI pair programming in your terminal. It lets you work with large language models to start a new project or build on an existing codebase, asking for changes in plain language and letting the model edit the files in your repository.

It builds a map of the whole codebase to help in larger projects, supports more than 100 programming languages and commits changes to git with descriptive messages, so you can diff or undo AI edits with familiar tools. It can connect to cloud models and local models, accept images and web pages as context, take voice instructions, and run linters and tests after each change, attempting to fix problems they report. It can also be used from an IDE through code comments, or via copy and paste with a model's web chat.

Aider is written in Python and licensed under Apache-2.0. The README names a handful of commercial models it has been used with most, but says it can connect to almost any model, and installation and usage guides are available in the documentation.

Tabby is an AI coding assistant that you host yourself, positioned as an on-premises, open-source alternative to GitHub Copilot. It is self-contained, so it needs no separate database management system or cloud service, and it exposes an OpenAPI interface that makes it easy to connect to existing infrastructure such as cloud IDEs.

It is designed to run on consumer-grade GPUs. Beyond code suggestions, the project has added a chat side panel, an Answer Engine whose conversations can be saved as shareable pages, the ability to switch between backend chat models, and the option to index repositories, your own documentation and GitLab merge requests as context. LDAP authentication and a VS Code extension with @-mentions for files are also covered in its updates.

Tabby is written in Rust and deployed on your own servers, which keeps source code and prompts inside your network. That suits organizations that cannot send code to a hosted service, and the docs, roadmap and a Slack community are linked from the repository.

Editor Code Assistant, or ECA, is a free open-source tool that brings AI pair programming to many code editors through a shared server and a well-defined protocol. The server is written in Clojure and is heavily inspired by the Language Server Protocol, with editors starting it as a subprocess and talking to it over standard input and output.

Because the logic lives in the server, features such as tool call management, interaction with multiple models, usage telemetry and configuration work the same way in every editor. ECA offers chat, rewrite and completion, multiple agents and subagents with different models and tools, context including MCP resources and prompts, and login to providers such as OpenAI, Anthropic, Copilot and local Ollama models. It can export OpenTelemetry metrics.

Official integrations exist for Emacs, VS Code, IntelliJ and a desktop app, and the protocol makes it easier for other editors to integrate. ECA is licensed under Apache-2.0 and runs on your own machine with your own model access. It suits developers and teams who want consistent AI assistance across editors.