9 open-source AI coding tools that every developer should know 🎯

AI is changing the world as we know it, and for developers, embracing it can significantly boost productivity. It helps you ship new features faster, write test cases for you, and even find vulnerabilities in your code.

The internet offers many tools, but finding the right one can take time and effort. So, I have compiled a list of AI tools to help you become a better developer.

👑: Opensource head-less IDE for Coding agents

As a developer, I have always wanted to build customized AI tools to let me chat with the codebase, automate pushing changes to GitHub, and ship new features automatically. Honestly, I couldn’t find a single tool until this.

SWE-Kit is a headless IDE with features like LSPs, Code Indexing, and Code RAG. It offers a flexible runtime, which can run on any Docker host or remote server alongside specialized coding toolkits.

These toolkits include integrations with platforms like GitHub, Jira, and Slack, as well as tools such as file search and code indexing, which Composio powers.

The coding agent built with SweKit has scored an impressive 48.60% on the verified

It is compatible with all the major LLM frameworks like LangChain, CrewAI, Autogen, and LlamaIndex.

You can build and deploy your own.

• GitHub PR Agent: This is used to automate the review of GitHub PRs.


• SWE Agent: You can build an SWE agent to write features, unit tests, documents, etc, automatically.


• Chat with Codebase: You can build a tool for chatting with any remote or local codebase using the code indexing tool.

Install swekit and composio-core to get started quickly.

pip install compsio-core swekit

Install any framework of your choice.

pip install crewai composio-crewai

Now, let’s create a Coding agent with GitHub access.

composio add github

Generate a new agent scaffolding.

swekit scaffold crewai -o swe_agent

Run the agent.

cd swe_agent/agent

python main.py

This uses Docker as the default workspace environment. For more, see the

- The AI Pair-programmer

This is the perfect choice if you're looking for a pair programmer to help you ship code faster.

Aider lets you pair programs with LLMs to edit code in your local GitHub repository. You can start a new project or work with an existing GitHub repo.

You can get started quickly like this:

pip install aider-chat



# Change the directory into a git repo

cd /to/your/git/repo



# Work with Claude 3.5 Sonnet on your repo

export ANTHROPIC_API_KEY=your-key-goes-here

aider



# Work with GPT-4o on your repo

export OPENAI_API_KEY=your-key-goes-here

aider

For more details, see the .

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: Tool for automated pull request analysis

This open-source tool from Codium AI automates GitHub Pull request review, analysis, feedback, and suggestions. It can help you become more productive with pull requests and is compatible with other version control systems like GitLab and BitBucket.

It has both self-hosted and cloud-hosted solutions.

You will need an OpenAI API key and a GitHub or GitLab access token for a self-hosted solution.

To use it locally, install the library.

pip install pr-agent

Then, run the relevant tool with the script below.

Make sure to fill in the required parameters (user_token, openai_key, pr_url, command):

from pr_agent import cli

from pr_agent.config_loader import get_settings



def main():

    # Fill in the following values

    provider = "github" # GitHub provider

    user_token = "..."  # GitHub user token

    openai_key = "..."  # OpenAI key

    pr_url = "..."      # PR URL, for example 'https://github.com/Codium-ai/pr-agent/pull/809'

    command = "/review" # Command to run (e.g. '/review', '/describe', '/ask="What is the purpose of this PR?"', ...)



    # Setting the configurations

    get_settings().set("CONFIG.git_provider", provider)

    get_settings().set("openai.key", openai_key)

    get_settings().set("github.user_token", user_token)



    # Run the command. Feedback will appear in GitHub PR comments

    cli.run_command(pr_url, command)



if __name__ == '__main__':

    main()

You can also use Docker images or run from the source. The

: Platform for AI software developer agents

OpenHands is one of the leading open-source platforms for AI agents and a direct competitor of Devin. An OpenHands agent can build new greenfield projects, add features to existing codebases, debug issues, and more.

Recently, their agent also topped the SWE-bench leaderboard with 53%.

To start with OpenHands, you need Docker version 26.0.0+ or Docker Desktop 4.31.0+ and Linux, Mac, or WSL.

Pull the docker image and run the container.

docker pull docker.all-hands.dev/all-hands-ai/runtime:0.12-nikolaik



docker run -it --rm --pull=always \

    -e SANDBOX_RUNTIME_CONTAINER_IMAGE=docker.all-hands.dev/all-hands-ai/runtime:0.12-nikolaik \

    -v /var/run/docker.sock:/var/run/docker.sock \

    -p 3000:3000 \

    --add-host host.docker.internal:host-gateway \

    --name openhands-app \

    docker.all-hands.dev/all-hands-ai/openhands:0.12

After running the command above, you'll find OpenHands running at 

They provide four methods for working with Agents: an interactive GUI, a command-line interface (CLI), and options for non-interactive use through headless mode and GitHub Actions. Each has its pros. For more, refer to the

: Coding assistant for IDEs

Cody is an open-source project from Sourcegraph designed to supercharge your coding workflow directly within your IDE—whether it's VS Code, JetBrains, or others. Cody leverages advanced search as a coding assistant to pull context from local and remote codebases. This enables seamless access to details about APIs, symbols, and usage patterns at any scale, right from your IDE.

With Cody, you can chat with your codebase, make inline edits, get code suggestions, and enjoy features like auto-completion, all tailored to help you code faster and more effectively.

You can simply install this on your IDEs and get started. For more, check the

: Chat with SQL database

I dread writing SQL queries, but at the same time, it is one of the most critical technologies in modern software development. Almost all companies heavily rely on SQL to interact with relational databases. But as they say, there is always an AI tool for it and SQL databases; it is Vanna AI.

It is an open-source tool that lets you chat with SQL databases using natural language.

Vanna works in two easy steps - train a RAG "model" on your data and then ask questions that will return SQL queries that can be set up to run on your database automatically.

 for more details.

Thanks for reading. If you use any other AI tool that has helped you, comment below.