LoRA -- MCP Tool Specification

Version: v1.1.9 | Status: Active | Last Updated: March 2026

Overview

This document defines the MCP tools exposed by the lora (Low-Rank Adaptation) module. These tools are auto-discovered by the PAI MCP bridge via the @mcp_tool decorator in mcp_tools.py and surfaced as part of the ~303 dynamic tools available to Claude.

Auto-Discovery

Property	Value
Discovery method	@mcp_tool decorator scan
Namespace	lora
Trust default	Safe
PAI bridge	src/codomyrmex/agents/pai/mcp/

Tool Reference

lora_apply

Description: Apply LoRA to a weight matrix of given shape. Trust Level: Safe Category: analysis

Parameters:

Parameter	Type	Required	Default	Description
weight_shape	list	Yes	--	[d, k] shape of the weight matrix
rank	int	No	4	LoRA rank r (must be < min(d, k))
alpha	float	No	8.0	LoRA scaling alpha

Returns: dict -- Dictionary with weight_shape, rank, scaling, lora_params, total_params, parameter_reduction_pct, and delta_shape.

Example:

from codomyrmex.lora.mcp_tools import lora_apply

result = lora_apply(weight_shape=[768, 768], rank=8, alpha=16.0)

Integration Notes

• Auto-discovered: Yes (via @mcp_tool in mcp_tools.py)
• Trust Gateway: All tools are safe -- no destructive operations
• PAI Phases: BUILD (adapter application), OBSERVE (parameter efficiency analysis)
• Dependencies: Requires numpy and internal lora module (apply_lora)

Navigation

• README.md | AGENTS.md | SPEC.md