This section describes how to deploy MindsDB from the source code. It is the preferred way to use MindsDB if you want to contribute to our code or debug MindsDB.

To successfully install MindsDB, use Python 64-bit version. Also, make sure that Python >= 3.8 and pip >= 20.3.


Please note that this method of MindsDB installation requires a minimum of 6 GB free storage.

  1. Clone the MindsDB repository:

    git clone
  2. Create a new virtual environment:

    python -m venv mindsdb-venv
  3. Activate the virtual environment:

    source mindsdb-venv/bin/activate
  4. Install dependencies:

    cd mindsdb
    pip install -e .
    pip install -r requirements/requirements-dev.txt
  5. Start MindsDB:

    python -m mindsdb

By default, MindsDB will always start the http and mysql APIs. If you want to use Mongo API, you will need to provide that as a parameter to --api. You can do it as follows:

python -m mindsdb --api=http,mongodb,mysql
  1. Now, you can access the following:


The dependencies for many of the data or ML integrations are not installed by default.

If you want to use a data or ML integration whose dependencies are not available by default, install it by running this command:

pip install '.[handler_name]'

You can find all available handlers here.


Pip and Python Versions

Currently, MindsDB supports Python versions 3.8.x, 3.9.x, 3.10.x, and 3.11.x.

To successfully install MindsDB, use Python 64-bit version. Also, make sure that Python >= 3.8 and pip >= 20.3. You can check the pip and python versions by running the pip --version and python --version commands.

Please note that depending on your environment and installed pip and python packages, you might have to use pip3 instead of pip or python3.x instead of py. For example, pip3 install mindsdb instead of pip install mindsdb.

How to Avoid Dependency Issues

Install MindsDB in a virtual environment using pip to avoid dependency issues.

How to Avoid Common Errors

MindsDB requires around 3 GB of free disk space to install all of its dependencies. Make sure to allocate min. 3 GB of disk space to avoid the IOError: [Errno 28] No space left on device while installing MindsDB error.

Before anything, activate your virtual environment where your MindsDB is installed. It is to avoid the No module named mindsdb error.

If you encounter the This site can’t be reached. refused to connect. error, please check the MindsDB server console to see if the server is still in the starting phase. But if the server has started and you still get this error, please report it on our GitHub repository.

How to Overcome ImportError: failed to find libmagic

If you get the ImportError: failed to find libmagic error, you should install the libmagic manually by running one of the commands below:

pip install python-magic-bin  # for linux and windows
brew install libmagic  # for macOS

Further Issues?

You can try to use Docker setup in case you are experiencing issues using pip.

Also, please create an issue with detailed description in the MindsDB GitHub repository so we can help you. Usually, we review issues and respond within a few hours.

What’s Next

Now that you installed and started MindsDB locally in your Docker container, go ahead and find out how to create and train a model using the CREATE MODEL statement. In the MindsDB SQL section, you’ll find a comprehensive overview of the SQL syntax offered by MindsDB. We also provide Mongo-QL syntax documented in the MindsDB Mongo-QL section.

You can connect MindsDB to different clients, including PostgreSQL CLI and MySQL CLI.

Check out the Use Cases section to follow tutorials that cover Large Language Models, Natural Language Processing, Time Series, Classification, and Regression models.