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@us-all/dbt-mcp

@us-all/dbt-mcp

by us-all
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TypeScript
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dbt-slow-models

List the slowest dbt models by execution time and bytes processed to identify performance bottlenecks.

Instructions

Top N slowest models in a dbt run by execution_time, with bytes_processed when available

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "dbt-slow-models"
  }
}

Input Schema

NameRequiredDescriptionDefault
topNNo
invocationIdNoUse a specific run; default is latest
extractFieldsNoComma-separated dotted paths to project from response (e.g. 'id,name,owner.name,columns.*.name'). Use `*` as wildcard for arrays/objects. Wrap field names with dots in backticks. Reduces response tokens dramatically on large entities.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.3
  2. Removedv1.0.2
  3. Changed1 schema field changedv1.0.0
    • addedInput schema / properties / extractFields
      Added value: +{
+  "description": "Comma-separated dotted paths to project from response (e.g. 'id,name,owner.name,columns.*.name'). Use `*` as wildcard for arrays/objects. Wrap field names with dots in backticks. Reduces response tokens dramatically on large entities.",
+  "type": "string"
+}
  4. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description is the sole source of behavioral information. It states the tool reads from a dbt run and returns a list, but does not disclose if it is read-only, permissions needed, or any rate limits. Critical behavioral traits are missing.

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 sentence that is concise and front-loaded, containing only essential information without extraneous details.

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's simplicity and lack of output schema or annotations, the description is adequate but incomplete. It does not mention how to use invocationId or extractFields, nor explain response format. Additional context would improve completeness.

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 input schema covers two of three parameters (invocationId, extractFields) with descriptions. The topN parameter is inferred from the tool's purpose but lacks explicit schema description. The tool description adds minimal value beyond the schema, so a baseline 3 is appropriate.

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 communicates that the tool returns the top N slowest models from a dbt run, sorted by execution_time. However, it lacks an explicit verb like 'list' or 'get', and while it distinguishes from sibling tools by focusing on slow models, it could be more precise.

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?

No guidance is provided on when to use this tool versus alternatives such as dbt-list-models or dbt-get-model. The description does not mention appropriate contexts or when not to use it.

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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