Start here
Inspect Python code, compare experiments or share selected functions through REST and MCP. Choose the result you need.
Choose your first result
| You want to… | Start with |
|---|---|
| Understand a script or notebook | Inspect an experiment |
| Call a Python function from another application | REST and MCP quickstart |
| Compare training attempts | Fraud experiment example |
| Hand over a generated service | Operations guide |
Install for the action you chose
Install Apizr with Python 3.11–3.15 on macOS or Linux.
Then save example.py:
learning_rate = 0.05
Inspect it:
apizr experiment inspect example.py
The report shows learning_rate = 0.05 under Parameters, without running the code.
Continue with your own work
- User guide: inspect, track and compare experiments.
- Developer guide: integrate Apizr with your tools.
- Examples: complete files and expected results.
- Reference: exact commands and options.
- Architecture: components and diagrams.
What the two MCP workflows do
The analysis MCP plugin lets a client inspect your project. A generated MCP server lets a client call the Python functions you selected.