Neural -- MCP Tool Specification

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

Overview

This document defines the MCP tools exposed by the neural 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	neural
Trust default	Safe
PAI bridge	src/codomyrmex/agents/pai/mcp/

Tool Reference

transformer_encode

Description: Run a forward pass through a randomly-initialized Transformer encoder. Trust Level: Safe Category: analysis

Parameters:

Parameter	Type	Required	Default	Description
sequence_length	int	No	8	Number of tokens in the sequence
d_model	int	No	64	Model dimension (must be divisible by n_heads)
n_heads	int	No	4	Number of attention heads
n_layers	int	No	2	Number of transformer blocks

Returns: dict -- Dictionary with output_shape, d_model, n_heads, n_layers, sequence_length, and status.

Example:

from codomyrmex.neural.mcp_tools import transformer_encode

result = transformer_encode(sequence_length=16, d_model=128, n_heads=8, n_layers=4)

---

attention_forward

Description: Run multi-head attention on random inputs. Trust Level: Safe Category: analysis

Parameters:

Parameter	Type	Required	Default	Description
seq_len	int	No	6	Sequence length
d_model	int	No	32	Model dimension
n_heads	int	No	4	Number of attention heads

Returns: dict -- Dictionary with output_shape, attention_weights_shape, d_k (head dimension), and status.

Example:

from codomyrmex.neural.mcp_tools import attention_forward

result = attention_forward(seq_len=10, d_model=64, n_heads=8)

Integration Notes

• Auto-discovered: Yes (via @mcp_tool in mcp_tools.py)
• Trust Gateway: All tools are safe -- no destructive operations
• PAI Phases: BUILD (neural network operations), VERIFY (architecture validation)
• Dependencies: Requires numpy and internal transformer module (TransformerEncoder) and attention module (MultiHeadAttention)

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