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Agent Cam MCP Tool

Agent Cam MCP Tool

by skr-electronics-lab
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

rectify_region

Correct perspective distortion in angled hardware or screen captures, returning a flat top-down image for precise inspection or OCR.

Instructions

Capture and perspective-correct (unwarp/rectify) an angled hardware region or screen into a flat, orthogonal top-down image. Returns the rectified image for high-precision inspection or OCR.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "region": "<region>"
    },
    "name": "rectify_region"
  }
}

Input Schema

NameRequiredDescriptionDefault
cameraNoCamera ID (default: primary camera)
formatNoImage format (default jpeg)jpeg
regionYesName of the defined region to rectify

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses the core transformation and that an image is returned, but omits key operational facts: that the named region must already be defined, what happens if the region is unknown, whether a fresh frame is captured, and any camera/prerequisite constraints.

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

Conciseness5/5

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

Two tight sentences: the transformation is front-loaded and the return value follows. No filler, no repetition of the name or schema.

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

Completeness4/5

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

For a 3-parameter tool with full schema coverage and no output schema, the description covers what the tool does and what it returns. The main gap is the unstated dependency on a pre-defined region and absence of any failure/edge-case behavior, which matters given the lack of annotations.

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

Parameters3/5

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

Schema description coverage is 100%, so camera, format, and region are already documented in the schema. The description adds nothing parameter-specific (no naming/format rules for the region, no camera selection guidance), so the baseline 3 applies.

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

Purpose4/5

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

The description gives a concrete compound verb (capture and perspective-correct/unwarp) and a specific resource (an angled hardware region or screen), plus the resulting artifact (a flat, orthogonal top-down image). This inherently separates it from capture_image and define_region, but no sibling is named explicitly, so it lands at clear-but-not-differentiating.

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

Usage Guidelines3/5

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

It implies the use case ('for high-precision inspection or OCR') but never states when to prefer this over capture_image or that a region must first exist via define_region. Usage is only inferable from the stated purpose, not spelled out with alternatives or exclusions.

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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