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netcare-io

jira-xray-cloud-mcp

by netcare-io

Xray Import Tests Bulk

xray_import_tests_bulk

Starts an asynchronous bulk import of up to 1,000 Xray tests, returning a job ID to poll with xray_get_import_tests_status for completion.

Instructions

Start an asynchronous bulk import of Tests. Poll xray_get_import_tests_status with the returned jobId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
testsYesTests to create/update (max 1000). Each: {'testtype': 'Manual'|'Cucumber'|'Generic', 'fields': {'summary': ..., 'project': {'key': ...}}, 'steps': [{'action','data','result'}], 'gherkin_def': ..., 'unstructured_def': ..., 'xray_test_repository_folder': '/path', 'xray_test_sets': [...], 'xray_preconditions': [...], 'update': {...}}.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false), so the bar is lower. The description still adds real value by disclosing that the operation is asynchronous and that it returns a jobId to be polled, which the annotations do not convey.

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?

Two short sentences, front-loaded with the action and then the required follow-up step. No filler or redundancy.

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?

An output schema exists, so return values need not be described, and the async polling requirement is captured. Only minor gaps remain, such as how partial failures or the 1000-item limit are reported back to the caller.

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 single 'tests' parameter is documented in exhaustive detail in the schema itself. The description adds nothing about parameter shape, so the baseline of 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?

States a specific verb (import), resource (Tests) and scope (bulk, asynchronous). The word 'bulk' implicitly separates it from the single-record sibling xray_create_test, but no sibling is named explicitly, so it falls short of a 5.

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

Usage Guidelines3/5

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

Gives a follow-up workflow (poll xray_get_import_tests_status with the returned jobId), which is useful operational guidance, but never states when to prefer this bulk tool over xray_create_test or the other import variants (cucumber, execution results). Usage is implied rather than framed as a choice.

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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