Apizr

An open-source capability compiler for Python codebases.

Discover capabilities in existing Python code, assess their static readiness, explicitly choose what to expose, generate REST or MCP interfaces, and run them under direct or governed execution policies.

Latest published stable: 0.3.0 · Released 22 September 2026

Python 3.11–3.14 · GPL-3.0-or-later. Install with python -m pip install outerspace-apizr==0.3.0. It adds explicit Exposure Plans and multi-module repository bundles. Discovery, generation, direct servers and governed local workers need no Docker.

Try the repository walkthrough Read the 0.3 release notes

From Python code to REST and MCP

Bring existing Python expertise into your applications and AI workflows. See how Apizr turns a route optimizer into callable interfaces.

▶ Watch the demo

English narration · English captions

Read the transcript

Put your business logic to work. For an operations team, time on the road matters. Your Python code already plans better routes. Apizr helps make that expertise available to the people and systems that need it.

Keep the expertise you already have. Here, a specialist has prepared a route optimizer in a notebook. The next step is to connect it to the dispatch application, using the same calculation.

Understand what you can expose. First, inspect the notebook with Apizr. It identifies the functions and reports which can generate an interface. Your team chooses the capability to make available.

Connect your operational applications. Select the route optimizer and generate REST. Apizr creates the application and its API contract. The dispatch system now has an interface it can call.

Generated code your team can inspect. These are the generated files. Your developers can inspect and run them. The adapter connects incoming requests to your existing function, keeping the business calculation in one place.

Put the generated API to work. Start the generated application and send a list of stops. The response contains a proposed route and its driving estimate. This is what the dispatch interface will use.

See the operational impact. Now the result becomes visible. On this eight-stop example, the estimated driving time drops from about one hundred and one minutes to forty eight.

Adapt when the workload changes. For a different twelve-stop tour, call the same API again. The route changes, with a fifty four percent improvement over this starting order. These estimates do not include live traffic.

Make the same capability available to AI. Next, use Apizr to generate an MCP server from the same function. An assistant can use the existing calculation as a tool, rather than estimate the route itself.

Turn a business request into an action. Ask Ollama to add the Pantheon while keeping the existing stops. Our local interface passes the generated tool definition to the model, then forwards its chosen call through MCP.

The same logic serves another channel. The tool returns a thirteen-stop tour. The map updates from that result. The application and the assistant now use the same underlying business logic.

Existing expertise. New applications. Inspect your Python. Choose what to expose. Generate REST and MCP interfaces with Apizr. Bring existing expertise into your applications and AI workflows.

Discover → Understand → Assess

apizr scan . inventories Python source without executing it. apizr graph . explains static relationships. apizr readiness . evaluates evidence under policy. Unknown evidence remains unknown; READY does not mean exposed.

Select → Expose

apizr expose plan records your explicit capability selection. apizr expose build creates one repository REST or MCP server. If selected A calls helper B, B is packaged as support and stays private. Plan exposure.

Execute with an explicit boundary

Mode	Boundary	State
Direct	Transport process	Persists
Governed local	Fresh process per call	Resets
Governed OCI	Fresh container per call	Resets

Local execution provides bounds and cleanup without filesystem/network isolation. OCI adds reviewed container controls with an explicit immutable worker image; it is not a VM or an untrusted-code guarantee. The optional strict OCI profile prohibits process/thread creation. Source and application dependencies must be trusted. Understand execution boundaries.

Single-source scripts/notebooks and the legacy pipeline remain supported. Previous 0.2.1 notes · Compatibility and migration.