# mixpanel_headless

> Python library for working with Mixpanel analytics data, designed for AI coding agents

mixpanel_headless is a complete programmable interface to Mixpanel analytics.
Python library and CLI for discovery, querying, streaming, and entity management.
Discover your schema, run live analytics (segmentation, funnels, retention, flows),
execute JQL, and stream data for processing.


## Getting Started

- [Home](https://mixpanel.github.io/mixpanel-headless/index.md): Project overview and key concepts
- [Installation](https://mixpanel.github.io/mixpanel-headless/getting-started/installation/index.md): Install with pip or uv
- [Quick Start](https://mixpanel.github.io/mixpanel-headless/getting-started/quickstart/index.md): First queries in 5 minutes
- [Configuration](https://mixpanel.github.io/mixpanel-headless/getting-started/configuration/index.md): Accounts, env vars, config files

## User Guide

- [The Unified Query System](https://mixpanel.github.io/mixpanel-headless/guide/unified-query-system/index.md): Unified query system — one vocabulary, four analytics engines
- [Data Discovery](https://mixpanel.github.io/mixpanel-headless/guide/discovery/index.md): Explore schema, events, properties, cohorts
- [Insights Queries](https://mixpanel.github.io/mixpanel-headless/guide/query/index.md): Typed insights queries — DAU, formulas, filters, breakdowns
- [Funnel Queries](https://mixpanel.github.io/mixpanel-headless/guide/query-funnels/index.md): Typed funnel queries — steps, exclusions, conversion windows
- [Retention Queries](https://mixpanel.github.io/mixpanel-headless/guide/query-retention/index.md): Typed retention queries — event pairs, custom buckets, alignment modes
- [Flow Queries](https://mixpanel.github.io/mixpanel-headless/guide/query-flows/index.md): Typed flow queries — path analysis, direction controls, visualization modes
- [User Profile Queries](https://mixpanel.github.io/mixpanel-headless/guide/query-users/index.md): Typed user profile queries — filtering, sorting, parallel fetching, aggregate counts
- [Live Analytics](https://mixpanel.github.io/mixpanel-headless/guide/live-analytics/index.md): Segmentation, funnels, retention, JQL
- [Streaming Data](https://mixpanel.github.io/mixpanel-headless/guide/streaming/index.md): Stream events and profiles for ETL
- [Entity Management](https://mixpanel.github.io/mixpanel-headless/guide/entity-management/index.md): Create, update, delete dashboards, reports, and cohorts
- [Data Governance](https://mixpanel.github.io/mixpanel-headless/guide/data-governance/index.md): Manage Lexicon definitions, drop filters, custom properties, custom events, lookup tables, schema registry, enforcement, auditing, anomalies, and event deletion requests
- [Business Context](https://mixpanel.github.io/mixpanel-headless/guide/business-context/index.md): Read and write the markdown business context that grounds AI assistants (org and project scopes, 50,000-char cap)

## API Reference

- [Overview](https://mixpanel.github.io/mixpanel-headless/api/index.md): Python API overview
- [Workspace](https://mixpanel.github.io/mixpanel-headless/api/workspace/index.md): Workspace class - main entry point
- [Auth](https://mixpanel.github.io/mixpanel-headless/api/auth/index.md): Authentication and credentials
- [Exceptions](https://mixpanel.github.io/mixpanel-headless/api/exceptions/index.md): Exception hierarchy
- [Result Types](https://mixpanel.github.io/mixpanel-headless/api/types/index.md): Result types (SegmentationResult, etc.)

## CLI Reference

- [Overview](https://mixpanel.github.io/mixpanel-headless/cli/index.md): CLI overview and output formats
- [Commands](https://mixpanel.github.io/mixpanel-headless/cli/commands/index.md): Complete command reference

## Architecture

- [Design](https://mixpanel.github.io/mixpanel-headless/architecture/design/index.md): Layered architecture and services