> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pysquirrels.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Welcome to Squirrels - The data analytics API framework for the AI era

Squirrels is a low-code API server framework for building data analytics APIs.

## Why Squirrels?

Want to serve well-described dynamic datasets to AI agents? Squirrels has you covered! Simply create a Squirrels project by writing data models in SQL and configurations in YAML (and/or Python for both). Activate the API server with the CLI and use the built-in MCP server for AI agents to interact with your data safely and efficiently.

No need to reinvent the wheel for building agent tools, serving dataset metadata, and creating token-efficient responses for tabular data!

## Highlights

* 🤖 **AI-Ready Architecture**: Built-in MCP server for serving dataset metadata and results to AI agents via token-efficient MCP tools.
* 🚀 **Low-Code REST API Development**: Create data analytics APIs using basic data engineering skills without extensive AI or backend engineering expertise.
* 🔌 **Connect Any Database**: Connect to any database or data warehouse that is supported by SQLAlchemy, ConnectorX, or ADBC.
* 📊 **Flexible Data Modeling**: Write data models that can reference other data models using Jinja-templated SQL or Python.
* 🔗 **Multi-Database Joins**: Connect to multiple databases in a single project and join data across sources in a single dataset!
* ⚙️ **Interactive Parameters**: Create dynamic datasets and dashboards that respond to user inputs and selections.
* 🔒 **Built-in Security**: Authentication and dataset permissions, with either Squirrels-managed users/API keys or external OAuth-based authentication.
* 💻 **Simple Developer Experience**: Quick setup with CLI commands `pip install squirrels` and `sqrl init`.

## Example projects

Check out these example Squirrels projects to see what you can build:

* [sqrl-expenses-slim](https://github.com/squirrels-analytics/squirrels-examples/tree/main/sqrl-expenses-slim): demonstrates the minimum setup needed for a practical working Squirrels project by storing expense transactions as a seed
* [sqrl-expenses](https://github.com/squirrels-analytics/squirrels-examples/tree/main/sqrl-expenses): an instance of a Squirrels project for expenses analytics that can be created with `sqrl init`
* [sqrl-mortgage-analysis](https://github.com/squirrels-analytics/squirrels-examples/tree/main/sqrl-mortgage-analysis): a Squirrels project for mortgage analytics that uses Python data models to perform Monte Carlo simulations
* [sqrl-weather-analytics](https://github.com/squirrels-analytics/squirrels-examples/tree/main/sqrl-weather-analytics): an extension of the tutorial example that includes joining data from multiple sources and realtime inference with a linear regression model

## Getting started

Start here if you are new to Squirrels! Follow these guides to learn how to use Squirrels quickly:

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/quickstart">
    Create a new working Squirrels project from scratch quickly
  </Card>

  <Card title="Complete the Tutorial" icon="graduation-cap" href="/tutorial">
    Follow a step-by-step tutorial to build your first custom Squirrels application
  </Card>
</CardGroup>

## Join the community

Got any questions or feedback? Feel free to send an email to [support@pysquirrels.com](mailto:support@pysquirrels.com).

Or come join us on our [Discord server](https://discord.gg/AXYn9rxTgP)!