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SWMM-MCP

SWMM-MCP

by kLabUM
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_report_sections

Retrieve available sections from SWMM model report files to analyze stormwater simulation results and understand hydraulic system behavior.

Instructions

Returns a list of sections in the report file for a given model.

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": {
      "model_name": "<model_name>"
    },
    "name": "get_report_sections"
  }
}

Input Schema

NameRequiredDescriptionDefault
model_nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns a list, implying a read-only operation, but doesn't cover aspects like error handling, rate limits, authentication needs, or the format of the returned sections. This leaves significant gaps in understanding the tool's behavior.

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 a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and appropriately sized for its simple function.

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 the tool has one parameter and an output schema exists, the description is somewhat complete but lacks depth. It doesn't explain the relationship to sibling tools or provide behavioral context, which is needed since no annotations are present. The output schema may cover return values, but overall completeness is minimal.

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?

The schema description coverage is 0%, so the description must compensate. It mentions 'for a given model', which implies the 'model_name' parameter is required, but doesn't explain what constitutes a valid model name or provide examples. This adds minimal semantic value beyond the basic schema.

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 clearly states the action ('Returns a list of sections') and resource ('in the report file for a given model'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_report_info' or 'get_input_sections', which likely serve related but different purposes.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for usage, or how it differs from sibling tools such as 'get_report_info' or 'get_input_sections', leaving the agent without clear usage instructions.

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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