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Polarion MCP Server

Polarion MCP Server

by phillipboesger
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TypeScript
Hybrid

patchTestRunComments

Idempotent

Update a batch of Test Run comments in a Polarion project, with optional dry-run validation to preview the request before sending.

Instructions

Updates a list of Test Run Comments. Cardinality: targets the full collection or a batch. For a single item by ID, use patchTestRunComment instead. Effect: idempotent — calling it again with the same input leaves the resource in the same end state, with no additional side effects. Tip: set dry_run: true first to validate the arguments and preview the exact request without sending it to Polarion. The executor returns this preview as normal text, and as structured content when the tool declares an output schema.

Input Schema

NameRequiredDescriptionDefault
dry_runNoIf true, validates the request and returns the exact request that would be sent to Polarion — with the Authorization header redacted and any binary payload summarized by byte length — without actually sending it.
projectIdYesThe Polarion project ID (its URL segment, e.g. `myproject`), case-sensitive. Required to scope the request to one project. If the ID is unknown, ask the user; getProjects lists IDs only with global read access.
testRunIdYesThe Test Run's ID within its project.
requestBodyYesThe Comment body.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.4.4
    • changedInput schema / properties / projectId / description
      Previous value: -"The Polarion project ID (its URL segment, e.g. `myproject`), case-sensitive. Required to scope the request to one project; call getProjects to list valid IDs."New value: +"The Polarion project ID (its URL segment, e.g. `myproject`), case-sensitive. Required to scope the request to one project. If the ID is unknown, ask the user; getProjects lists IDs only with global read access."
  2. Changed3 schema fields changedv1.2.0
    • changedInput schema / properties / dry_run / description
      Previous value: -"If true, validate and return the request that would be sent without calling Polarion."New value: +"If true, validates the request and returns the exact request that would be sent to Polarion — with the Authorization header redacted and any binary payload summarized by byte length — without actually sending it."
    • changedInput schema / properties / projectId / description
      Previous value: -"The Project ID."New value: +"The Polarion project ID (its URL segment, e.g. `myproject`), case-sensitive. Required to scope the request to one project; call getProjects to list valid IDs."
    • changedInput schema / properties / testRunId / description
      Previous value: -"The Test Run ID."New value: +"The Test Run's ID within its project."
  3. Changed1 schema field changed
    • addedInput schema / properties / dry_run
      Added value: +{
+  "description": "If true, validate and return the request that would be sent without calling Polarion.",
+  "type": "boolean"
+}
  4. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare idempotentHint=true, destructiveHint=false, and readOnlyHint=false, and the description's idempotency sentence largely restates that. The dry_run preview workflow is useful context, but its details are duplicated verbatim from the parameter schema, so value added beyond structured fields is modest.

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?

Front-loaded with purpose and cardinality, then alternative and behavioral notes, which is a sound ordering. The closing clause about structured content 'when the tool declares an output schema' is conditional boilerplate since no output schema exists here.

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 batch mutation with nested request bodies, the description covers cardinality, idempotency, the singular alternative, and the dry-run safety workflow, which is enough to call it correctly given annotations and full schema coverage. It omits what the bulk operation does on partial failure, the only meaningful remaining 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%, so all four parameters, including the nested requestBody, are documented in the schema itself. The description only reinforces that the payload is a list and points at dry_run; it adds no syntax or field-level meaning (e.g., that only `resolved` is settable) beyond the schema.

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 uses a specific verb and resource ('Updates a list of Test Run Comments') and immediately disambiguates cardinality ('targets the full collection or a batch') against the singular sibling `patchTestRunComment`. An agent can pick between the two without opening either schema.

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

Usage Guidelines4/5

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

It explicitly routes single-item updates to `patchTestRunComment` and recommends a `dry_run: true` validation call first, which is clear operational guidance. It stops short of stating when-not-to-use cases (e.g., bulk vs. batch size limits or permission prerequisites).

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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