Use via MCP

axm-init exposes its CLI commands as MCP (Model Context Protocol) tools via axm-mcp. AI agents can call them directly without spawning subprocesses.

Available Tools

MCP Tool	Equivalent CLI	Purpose
init_check	axm-init check	Score a project, returns context (standalone/workspace/member)
init_scaffold	axm-init scaffold	Scaffold a project, workspace, or member package
init_reserve	axm-init reserve	Reserve a package name on PyPI

Usage

MCP dispatch

The examples below show the logical API — the parameters and return values. In practice, AI agents call these via MCP tool dispatch (e.g. mcp_axm-mcp_init_check), not direct Python imports.

Check a project

Python

# MCP tool call (not importable — dispatched by axm-mcp)
result = mcp_axm_mcp_init_check(path="/path/to/project")

Returns the same structured output as axm-init check --agent — passed checks summarized, failed checks with full detail and fix hints.

Scaffold a project

Python

# MCP tool call (not importable — dispatched by axm-mcp)
result = mcp_axm_mcp_init_scaffold(
    path="/path/to/new-project",
    name="my-project",
    org="my-org",
    author="Your Name",
    email="you@example.com",
    workspace=True,   # or member="my-lib"
)

Reserve a package name

Python

# MCP tool call (not importable — dispatched by axm-mcp)
result = mcp_axm_mcp_init_reserve(name="my-package", author="Your Name", email="you@example.com")

Entry Points

The tools are registered via pyproject.toml entry points:

TOML

[project.entry-points."axm.tools"]
init_check    = "axm_init.tools.check:InitCheckTool"
init_scaffold = "axm_init.tools.scaffold:InitScaffoldTool"
init_reserve  = "axm_init.tools.reserve:InitReserveTool"

axm-mcp discovers these automatically at startup.