7 Best Open Source AI Coding Agents in 2026

What Counts as an Open Source AI Coding Agent

Most roundups call anything with a free tier "open source." That misses the point. For this list, an open source AI coding agent must meet three conditions.

First, the license. The tool must ship under an OSI-approved license like MIT or Apache-2.0. That means you can fork it, modify it, and run it on your own infrastructure without asking permission. A source-available license with restrictions on commercial use does not qualify.

Second, self-hosting. You should be able to run the agent on your own machine or server, not just inside a vendor's cloud. This usually means the agent is a CLI tool or an IDE extension that talks to models through your own API keys.

Third, local model support. The agent should work with models you run yourself, like those served through Ollama or vLLM, not just with a vendor's hosted API. This matters for privacy, cost control, and offline work.

Enterprise tools like GitHub Copilot do not make this list. Copilot is proprietary, closed-source, and tied to GitHub's infrastructure. You cannot fork it or run it with your own models. The same applies to most commercial assistants from the big AI labs. They may be useful, but they are not open source.

This list covers seven agents that meet the bar. They range from terminal-first tools to IDE extensions, and they all let you bring your own API keys or run local models.

The 7 Best Open Source AI Coding Agents in 2026

1. Aider

Aider is a terminal-based pair programmer. It runs in your command line and works directly with your Git repository. The core idea is that Aider makes commits for you, so every change is tracked and reversible. You describe a change in plain language, and Aider edits the code and commits it with a sensible message.

Git integration is the standout feature. Aider reads your repo's Git history to understand context, and it can automatically commit changes after each edit. That makes it easy to review what the AI did and roll back if something breaks. The docs describe support for multiple models, including the OpenAI and Anthropic families, and you can point it at a local model via an OpenAI-compatible endpoint.

Aider has a strong reputation on benchmarks like SWE-bench, though exact scores change as models improve. The project is actively maintained, with regular releases and a responsive maintainer. If you live in the terminal and want a no-frills assistant that respects your Git workflow, Aider is a solid choice.

One limitation: Aider is not an IDE. It has no graphical interface, no file explorer, no debugger integration. You need to be comfortable with the command line. For many developers that is a feature, not a bug.

2. Cline

Cline is a VS Code extension that brings an AI coding agent into your editor. It supports both local and remote models, so you can use anything from a hosted API to a model running on your own machine. Cline's interface shows a chat panel alongside your code, and it can read and edit files, run terminal commands, and browse documentation.

The standout feature is the plan/act modes. In plan mode, Cline analyzes your request and proposes a set of changes without touching your files. You review the plan, approve it, and then switch to act mode to execute. This two-step flow reduces the risk of the AI making unwanted changes. It is especially useful for larger refactors where you want to see the approach before committing.

Cline is built on the open source model of VS Code extensions, and its repository is available on GitHub. It has a large user base, and the project is actively developed. The docs highlight support for MCP servers, which lets you connect Cline to external tools and data sources.

The main downside is that Cline is tied to VS Code. If you use another editor, you are out of luck. Also, the plan/act workflow can feel heavy for small edits, where you just want a quick answer.

3. OpenCode

OpenCode is a terminal-based agent that focuses on long-running tasks. It is designed to handle multi-step workflows where the agent needs to maintain context over many turns. OpenCode supports multiple models, and you can switch between them mid-session.

The key differentiator is session management. OpenCode keeps a conversation history and lets you resume tasks across sessions. That makes it good for large refactors or debugging sessions that span hours or days. The docs describe a client-server architecture, which means you can run the agent on a remote machine and connect from your local terminal.

OpenCode is written in TypeScript and is available under a permissive license. It has a growing community, and the repository shows active development. If you need an agent that can grind through a complex task without losing context, OpenCode is worth a look.

One caveat: OpenCode is younger than Aider or Cline, so the ecosystem of plugins and integrations is smaller. You may need to configure more things yourself.

4. Roo Code

Roo Code started as a fork of Cline and has grown into its own project. It is a VS Code extension that adds custom modes and deeper orchestration. Where Cline has plan and act modes, Roo Code lets you define your own modes with specific instructions and allowed tools.

For example, you can create a mode for writing tests, another for refactoring, and another for reviewing code. Each mode can have its own system prompt and tool permissions. This is powerful for teams that want to standardize how the AI behaves for different tasks.

Roo Code also supports MCP servers and can orchestrate multiple agents in a single session. The docs describe a feature called "orchestration" where you can chain tasks across modes. That makes it suitable for complex workflows that involve multiple steps and multiple files.

Because it is a fork, Roo Code shares much of Cline's DNA, but it has diverged significantly. The project is actively maintained, and the repository shows a steady stream of commits. If you want more control over the agent's behavior than Cline offers, Roo Code is a strong candidate.

The downside is that Roo Code can be more complex to configure. The custom mode system has a learning curve, and you may spend time tweaking prompts before the agent behaves as you want.

5. OpenManus

OpenManus is an open-source agent that does not depend on an IDE. It runs as a standalone CLI tool, and it is designed for general coding tasks. You can ask it to write a script, fix a bug, or explain a piece of code, and it will do so using the model you configure.

The main appeal is simplicity. OpenManus has a minimal setup: install it, set your API key, and start asking questions. It does not require a specific editor or a complex configuration. That makes it a good entry point for people who want to try an AI coding agent without committing to a particular workflow.

OpenManus supports multiple models, and you can point it at a local model if you prefer. The project is relatively new, but it has gained attention for its straightforward approach. The repository shows active development, with frequent updates.

The trade-off is that OpenManus lacks the deep integration that IDE-based tools offer. It cannot see your open files or your editor's context, so you need to provide enough information in your prompts. For small tasks, that is fine. For large codebases, it can be limiting.

6. Goose

Goose is an agent from Block, the company behind Square. It is a block-based agent, meaning it works with a visual interface where you can see the steps the agent takes. Goose supports MCP servers, which lets you connect it to external tools and data sources.

Goose is designed to be extensible. You can add new tools and capabilities through MCP, and you can configure it to work with different models. The docs describe support for local models as well as hosted APIs.

The block-based interface is unusual among coding agents. Instead of a simple chat, you see a sequence of actions, like file edits and command executions, displayed as blocks. This gives you a clear view of what the agent is doing, which can be reassuring when it is making changes to your code.

Goose is open source and available on GitHub. It has a corporate backer, which means it is likely to receive ongoing support. However, the block-based UI may feel unfamiliar if you are used to a chat interface.

7. Continue

Continue is an open-source IDE assistant and agent that focuses on extensibility. It works as an extension for VS Code and JetBrains IDEs, and it provides both autocomplete and agentic features. You can use it for quick completions or for larger tasks that involve multiple files.

The key strength is the ability to customize almost everything. Continue lets you define your own models, prompts, and even custom slash commands. It supports MCP servers, so you can connect it to your own tools. The docs describe a configuration file where you can set up different model profiles for different tasks.

Continue is built with a modular architecture, and it has a plugin system that allows you to extend its functionality. The project is actively maintained, and the repository shows a large community.

One limitation is that Continue's agentic mode is less mature than some of the dedicated agents on this list. It is strong at autocomplete and inline assistance, but for complex multi-step tasks, tools like Cline or Roo Code may be more capable.

Quick Comparison Table

Tool	License	Autocomplete vs Agentic	IDE/Terminal	Local Model Support	GitHub Stars
Aider	Apache-2.0	Agentic	Terminal	Yes	~25k
Cline	Apache-2.0	Agentic	VS Code	Yes	~30k
OpenCode	MIT	Agentic	Terminal	Yes	~15k
Roo Code	Apache-2.0	Agentic	VS Code	Yes	~12k
OpenManus	MIT	Agentic	Terminal	Yes	~20k
Goose	Apache-2.0	Agentic	Terminal/Desktop	Yes	~18k
Continue	Apache-2.0	Both	VS Code/JetBrains	Yes	~25k

Star counts are approximate and change frequently. They reflect community interest, not necessarily quality or maturity.

How to Choose: Contribution Activity, License, and Model Support

Before you install any of these tools, check three things.

First, contribution activity. A tool with a dead repository is a risk. Look at the commit history in 2026. Are there commits in the last month? Is the maintainer responsive to issues? A project with regular commits is more likely to fix bugs and keep up with model API changes. All seven tools on this list show active development, but the pace varies. Aider and Cline have the most consistent commit streams, while OpenManus and OpenCode are younger and may have more sporadic activity.

Second, license. Confirm the license is OSI-approved. MIT and Apache-2.0 are the most common. Apache-2.0 includes an explicit patent grant, which can be important for commercial use. MIT is simpler. Both are fine for most projects. Avoid tools with source-available licenses that restrict commercial use or require you to share your changes.

Third, model support. The whole point of an open source agent is that you can bring your own API keys or run local models. Check that the tool supports the model you want to use. Most support OpenAI and Anthropic models, and many support local models via Ollama or an OpenAI-compatible endpoint. If you plan to use a specific model, verify that the tool has been tested with it.

Also consider the interface. Do you prefer a terminal or an IDE? Terminal tools like Aider and OpenCode are lightweight and scriptable. IDE tools like Cline and Continue integrate with your editor's features, like code navigation and debugging. There is no right answer; it depends on your workflow.

Pricing and Self-Hosting Costs

The tools themselves are free. You can download, fork, and run them without paying a license fee. The cost comes from the models you use.

If you use hosted APIs, you pay per token. The pricing snapshot shows a wide range. For example, openai/o1-pro costs $150 per million input tokens and $600 per million output tokens. That is expensive. On the other end, openai/gpt-5-pro costs $15 per million input and $120 per million output. Anthropic's claude-opus-4.1 is $15 in and $75 out. These prices add up quickly if you run long agentic sessions that generate many tokens.

To control costs, you can use cheaper models for routine tasks and reserve the expensive ones for complex reasoning. Some tools let you configure multiple models and switch between them. For example, you might use a fast, cheap model for autocomplete and a powerful model for refactoring.

If you want to avoid API costs entirely, you can run local models. This requires hardware. A small model like a 7B parameter model can run on a modern laptop with 16GB of RAM, but it will be slow. A 70B model needs a high-end GPU with at least 24GB of VRAM, and even then, inference will be slower than a hosted API. Local models also tend to be less capable than the best hosted models, so you may see a drop in code quality.

Self-hosting the agent itself is trivial. These are CLI tools or IDE extensions that run on your machine. There is no server to maintain unless you want to run a central instance for a team. In that case, you would need to manage the infrastructure and the model endpoints.

Verdict: Which Should You Install

There is no single best tool. The right choice depends on your workflow.

If you live in the terminal and want a reliable pair programmer with strong Git integration, install Aider. It is mature, well-documented, and has a proven track record. The automatic commits are a killer feature for keeping your history clean.

If you use VS Code and want a visual agent with plan/act modes, install Cline. It is the most popular open source agent in this category, and the plan/act workflow gives you control over what the AI does.

If you need to automate long-running tasks or orchestrate multiple steps, consider Roo Code or OpenCode. Roo Code's custom modes give you fine-grained control, while OpenCode's session management is good for tasks that span multiple days.

If you want a simple, no-IDE agent for general coding tasks, OpenManus is a good starting point. It is easy to set up and does not require a specific editor.

If you want a visual, block-based interface and plan to use MCP servers, Goose is worth trying. It is backed by a large company, which may mean more long-term support.

If you want both autocomplete and agentic features in your IDE, Continue is a solid choice. It is highly extensible, and you can tailor it to your exact needs.

Ultimately, the best way to choose is to try two or three. They are all free and open source, so the only cost is your time. Start with the one that matches your primary editor and workflow, and switch if it does not fit.

How this review was researched

This review is based on public information: the official documentation for each tool, the repository pages on GitHub, and the live pricing data for AI models. No tools were installed or tested for this article. Star counts and commit activity are taken from the repositories and are approximate. Pricing figures come from the live model pricing snapshot provided by the publisher. For the most current information, check the official sources.