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LeCroy Oscilloscope MCP

by lucasgerads

scope_decode_read

Read decoded serial data from the scope's SerialDecode subsystem and export to a .npz file. Compatible with UART, I2C, SPI, CAN, and other serial protocols. Returns file path and metadata.

Instructions

Read decoded serial data from the scope's SerialDecode subsystem.

The scope must already have a serial decode active (configured via its UI or scope_decode_configure_uart). Works with UART/RS-232, I2C, SPI, CAN, and any other protocol supported by the Decode option.

Reads the decoded table row-by-row using the VBS Table API and saves the result to a timestamped .npz file so the raw data is not embedded in the response. The file contains: time_s — float array, timestamp for each decoded frame/byte data — uint8 array, decoded byte values

Returns JSON with the file path and metadata. Load in Python with: import numpy as np d = np.load('/path/to/file.npz') times, data_bytes = d['time_s'], d['data']

Note: row-by-row VBS queries are slow (~0.05 s each). Decodes with hundreds of rows will take 10–20 s. Keep this in mind for large captures.

Args: decoder: Decode slot number — 1 or 2 (default 1)

Transport: VBS (app.SerialDecode.Decode{n}.Out.Result.*)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
decoderNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description fully carries burden. Discloses row-by-row VBS slowness (~0.05 s each), typical duration for large decodes, file-saving behavior, return format, and Python loading instructions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections, front-loaded purpose. A few extra sentences could be tightened, but overall efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers prerequisites, output format, performance caveats, and loading instructions. No gaps given complexity and lack of annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Single parameter 'decoder' explained as slot number 1 or 2. Schema only has type and default (0% coverage), so description adds needed context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb+resource: 'Read decoded serial data from the scope's SerialDecode subsystem.' Distinguishes from siblings like scope_get_waveform or scope_write by focusing on decoded serial data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states precondition: 'The scope must already have a serial decode active' and names an alternative configure tool (scope_decode_configure_uart). Also warns about performance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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