What problem does it solve?
Setting up a Python environment for Mixpanel data analysis requires installing multiple packages and configuring credentials across service accounts, OAuth tokens, and regions, which is error-prone when done manually.
Core Features & Use Cases
- Dependency Installation: Installs mixpanel_headless, pandas, numpy, matplotlib, seaborn, networkx, anytree, scipy, and pyarrow on Python 3.11+ using uv or pip.
- Credential Verification: Checks service-account environment variables, OAuth bearer tokens, and persisted accounts in ~/.mp/config.toml, then reports session state as ok, needs_account, needs_project, or error.
- Remote Session Support: Detects sandboxed environments and guides users to export an auth bridge file from their host machine for credential access.
- Use Case: A data analyst starting Mixpanel event analysis in a fresh environment runs the setup script to install all libraries, then runs mp login to authenticate and confirms the connection with an account test.
Quick Start
Ask the assistant to set up the Mixpanel analytics environment and verify that credentials are configured correctly.
