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drawio-engineering-mcp

drawio-engineering-mcp

by RFingAdam
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JavaScript
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open_drawio_csv

Open a draw.io editor with a diagram generated from CSV data, using draw.io's CSV import format to create org charts, flowcharts, and other diagrams from tabular data.

Instructions

Opens the draw.io editor with a diagram generated from CSV data. The CSV format should follow draw.io's CSV import specification which allows creating org charts, flowcharts, and other diagrams from tabular data.

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": {
      "content": "<content>"
    },
    "name": "open_drawio_csv"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentYesThe CSV content following draw.io's CSV import format.
lightboxNoOpen in lightbox mode (read-only view). Default: false
darkNoDark mode setting. Default: auto

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states 'Opens the draw.io editor' without disclosing side effects, permissions, rate limits, or whether it is read-only or mutating. The lightbox parameter hints at read-only but is not explained.

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?

The description is two sentences with no wasted words. First sentence states purpose, second adds format context. Front-loaded with primary action.

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

Completeness3/5

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

Given no output schema and no annotations, the description could elaborate on return behavior or errors. It adequately covers purpose and parameter context but lacks guidance on what the tool returns or how it behaves.

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?

Schema coverage is 100% (all 3 parameters have descriptions). The description adds value by referencing 'draw.io's CSV import specification' for the content parameter, providing context beyond the schema. The lightbox and dark parameters are standard.

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?

The description clearly states 'Opens the draw.io editor with a diagram generated from CSV data', providing a specific verb and resource. It also distinguishes from siblings like open_drawio_xml or open_drawio_mermaid by specifying CSV data.

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

Usage Guidelines4/5

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

The description implies use for tabular data via CSV, saying 'allows creating org charts, flowcharts, and other diagrams from tabular data'. This gives context but does not explicitly mention when to use or avoid compared to siblings.

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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