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Teradata MCP Server

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by Teradata
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Python
Remote

Dba Userdelay

dba_userDelay
Read-onlyIdempotent

Reports query queue wait times for Teradata users, helping identify delays before execution begins.

Instructions

Report how long Teradata users waited in the query queue before their queries began executing. Use when the user asks about user wait times, queue delays, or how long users had to wait. For system-level throttling and workload management flow control events, use dba_flowControl instead.

Arguments: start_date - The start date for the query range in YYYY-MM-DD format. end_date - The end date for the query range in YYYY-MM-DD format. persist - If True, materializes result as a volatile table and returns table name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
persistNoIf True, materializes result as a volatile table and returns table name
end_dateYesThe end date for the query range in YYYY-MM-DD format.
start_dateYesThe start date for the query range in YYYY-MM-DD format.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.2.1
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / end_date / title
      Removed value: -"End Date"
    • addedInput schema / properties / persist
      Added value: +{
+  "default": false,
+  "description": "If True, materializes result as a volatile table and returns table name",
+  "type": "boolean"
+}
    • removedInput schema / properties / start_date / title
      Removed value: -"Start Date"
  2. Changed3 schema fields changedv1.0.0
    • addedInput schema / properties / end_date / description
      Added value: +"The end date for the query range in YYYY-MM-DD format."
    • addedInput schema / properties / start_date / description
      Added value: +"The start date for the query range in YYYY-MM-DD format."
    • removedInput schema / title
      Removed value: -"_dynamic_toolArguments"
  3. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds useful context about queue-based wait behavior and excludes flow control, but does not elaborate on aggregation, units, or response shape. This is adequate but not deeply transparent.

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?

The core guidance is front-loaded in two clear sentences followed by a sibling alternative. The argument list is slightly redundant given the schema already documents all parameters, but it is compact and does not undermine clarity.

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 read-only reporting tool with a simple date-range interface and no output schema, this description is largely complete: it states what is measured, when to use it, how to parameterize it, and which sibling to choose instead. It could mention what the returned data looks like, but this is a minor gap.

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%, and the description's argument list largely duplicates the schema text. It adds no new semantic meaning beyond what the schema already provides, so baseline 3 is appropriate.

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?

States a specific verb and resource: 'Report how long Teradata users waited in the query queue before their queries began executing.' It clearly distinguishes this tool from dba_flowControl by naming the sibling it is not.

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 tells the agent when to use this tool ('user wait times, queue delays, or how long users had to wait') and when to use dba_flowControl instead ('system-level throttling and workload management flow control events'). No inference is required.

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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