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qase-tms

Qase MCP Server

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by qase-tms

qase_get

Read-onlyIdempotent

Fetch a specific Qase record by type and ID—cases, suites, runs, defects, and more. Use when you already know the identifier and need a single entity with optional field filtering.

Instructions

Fetch one known record by type and ID: case, suite, run, result, plan, defect, milestone, environment, shared_step, shared_parameter, configuration, attachment, author, user, review, or custom_field. code is required for project-scoped entities and can be omitted for global ones (user, author, attachment, custom_field). Narrow the payload with fields, or pass ["*"] for everything. Use this only when you already know the ID and want a single record. For several records, for anything filtered or cross-project, or when you are about to call this in a loop, use qql_search instead — one search returns the whole page at once. Cost: one API call, 0.3-0.5s. Ten of these in sequence measured 5.3s against 1.2s for a single qql_search returning the same ten records, so a loop over IDs is roughly four times slower and ten times more calls.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesEntity ID (number) or hash (string)
codeNoProject code (required for most entities)
entityYesEntity type to fetch
fieldsNoOptional field projection — only return these top-level fields. Pass ["*"] for all fields.
includeNoComma-separated list of related entities to include in the response. Cases and runs already request their external issue links by default ("external_issues" / "external_issue"); pass this only to override that.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv2.2.1
    • changedInput schema / properties / entity / enum
      Previous value: -[
      -  "case",
      -  "suite",
      -  "run",
      -  "result",
      -  "plan",
      -  "defect",
      -  "milestone",
      -  "environment",
      -  "shared_step",
      -  "shared_parameter",
      -  "configuration",
      -  "attachment",
      -  "author",
      -  "user",
      -  "custom_field"
      -]New value: +[
      +  "case",
      +  "suite",
      +  "run",
      +  "result",
      +  "plan",
      +  "defect",
      +  "milestone",
      +  "environment",
      +  "shared_step",
      +  "shared_parameter",
      +  "configuration",
      +  "attachment",
      +  "author",
      +  "user",
      +  "review",
      +  "custom_field"
      +]
  2. Changed1 schema field changedv2.0.3
    • addedInput schema / properties / include
      Added value: +{
      +  "description": "Comma-separated list of related entities to include in the response. Cases and runs already request their external issue links by default (\"external_issues\" / \"external_issue\"); pass this only to override that.",
      +  "type": "string"
      +}
  3. Addedv2.0.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare the operation read-only, idempotent, and non-destructive, so the description doesn't need to repeat that. It adds useful behavioral context: one API call, measured latency, and a concrete performance penalty for doing this in a loop instead of using qql_search. It doesn't cover error/not-found behavior, but that is a minor gap given the strong annotation coverage.

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 front-loaded with the operation and entity list, followed by code requirements, then usage boundaries, then cost guidance. Every sentence earns its place, and the measured performance comparison directly supports the recommended routing to qql_search.

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 single-record fetch tool, the description covers scope, code requirements, field projection, and alternative routing, which is enough for correct selection and invocation. It could mention response/error shape and the include parameter more explicitly, but the schema covers include and annotations cover safety.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful nuance beyond the schema: code is required for project-scoped entities but can be omitted for global ones, and fields can be narrowed or set to ['*']. It does not add much about the include parameter, but the schema already documents that.

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 opens with a specific action and resource: 'Fetch one known record by type and ID', and enumerates all 16 supported entity types. This clearly distinguishes it from qql_search, which is for batched/filtered lookup, without requiring an agent to open the schema.

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?

The description gives an explicit selection rule: 'Use this only when you already know the ID and want a single record.' It names the alternative, qql_search, and lists the exact conditions that should route an agent away from this tool: several records, filtered or cross-project queries, or loops.

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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