Mito

Mito

Mito is an AI Jupyter Notebook platform for database connections, Excel automations, and data workflows. It runs as a Jupyter extension inside JupyterLab, JupyterHub, SageMaker, and other notebook environments, and also ships as a standalone Mito Desktop app for macOS, Windows, and Linux.

The core idea is simple: edit data in a familiar spreadsheet interface, and Mito writes the Python code for you. Every filter, pivot, formula, or formatting change becomes reusable production code. Mito AI adds chat, agent, and autocomplete features that understand your notebook cells, dataframe structure, and recent edits.

For enterprise teams, Mito runs entirely on your own infrastructure. You can bring your own LLM API keys through Azure, AWS, LiteLLM, or other providers so sensitive data never leaves your environment. The open source project lives on GitHub with active community contributions.

Mito is used by analysts automating Excel reports, data scientists doing exploratory analysis, and ML engineers building models faster. The site lists Fortune 500 customers across financial services and life sciences.

Top Features:
  1. Every spreadsheet edit generates reusable Python code behind the scenes

  2. Jupyter Agent, chat, and autocomplete that read your notebook and dataframe context

  3. Low-code SQL editor with Snowflake query builder and database connections

  4. Runs on your infrastructure with bring-your-own LLM keys for Azure, AWS, or LiteLLM

  5. Mito Desktop for macOS, Windows, and Linux, plus pip install for existing Python setups

  6. Connects to BigQuery, Snowflake, PostgreSQL, Excel, S3, Google Drive, and more

Pros:
  1. Open source core on GitHub with a free tier that includes 150 monthly AI completions

  2. Spreadsheet interface generates production Python code without manual pandas scripting

  3. Enterprise deployments run on your infrastructure with self-hosted LLM support

  4. Works in JupyterLab, Streamlit, Dash, and as a standalone desktop app

  5. Connects to Snowflake, BigQuery, PostgreSQL, Excel, S3, and other common data sources

Cons:
  1. Open source tier limits AI completions to 150 per month

  2. Enterprise database and LLM integrations require contacting the sales team

  3. VS Code and Google Colab installs require emailing the Mito team directly

  4. Some Pro and Enterprise features like shareable notebooks and script scheduling are marked coming soon

FAQs:

Is Mito free to use?

Mito Open Source is free and includes 150 AI completions per month, AI Chat, Agent, and Autocomplete, plus a basic Mito Spreadsheet. Mito Pro costs $20 per user per month with unlimited AI completions. Mito Enterprise is available through a sales conversation for teams needing admin controls and custom integrations.

How do I install Mito?

Mito installs as a Jupyter extension in JupyterLab, Jupyter Notebooks, JupyterHub, Streamlit, and Dash using pip install mito-ai mitosheet. You can also download Mito Desktop v1.0 for macOS, Windows, or Linux from the Mito downloads page.

Is Mito open source?

Yes. Mito is an open source project and the codebase is available on GitHub at mito-ds/mito. Outside contributions are welcome and encouraged.

Can Mito automate spreadsheet tasks?

Yes. Mito is designed for spreadsheet automation. Complete your workflow once in the Mito spreadsheet interface and Mito generates a Python script you can rerun on new data.

Does Mito connect to databases?

Yes. Mito includes a low-code SQL editor for writing database connection and SQL code through a visual interface. The site lists integrations with Snowflake, BigQuery, PostgreSQL, MySQL, Redshift, Databricks, and other data sources.

Can enterprises keep data on their own infrastructure?

Yes. Mito Enterprise runs fully on your infrastructure and supports self-hosted large language models so no data leaves your systems. Enterprise users can also connect custom databases and LLM providers.

Category:

Pricing:

Freemium

Tags:

Python Data Science
Spreadsheet Automation
Code Generation
Streamlit Dashboards
Jupyter Extension
Jupyter Notebook
Excel Automation
SQL
Open Source

Tech used:

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React
Amazon Web Services
Google Cloud
Google Analytics
Google Tag Manager
Segment
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Google Fonts
Python
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Discord
GitHub
Webpack

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