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Polarion MCP Server

by phillipboesger
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TypeScript
Hybrid

deleteCollections

DestructiveIdempotent

Delete multiple Polarion collections in one batch. Preview with dry_run first because deletion is irreversible and cannot be recovered via API.

Instructions

Deletes a list of Collections. Cardinality: targets the full collection or a batch. For a single item by ID, use deleteCollection instead. Effect: irreversible — data removed or overwritten by this call cannot be recovered through the API. Tip: set dry_run: true first to preview the exact request Polarion would receive, without changing anything. On tools with a typed output schema, this preview is returned as an error-flagged result since it is not real tool output -- read the text content regardless of that flag.

Input Schema

TableJSON 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; call getProjects to list valid IDs.
requestBodyYesThe Collection(s) body.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 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."
  2. Added

TDQS

A4.7/5.0
Behavior5/5

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

While annotations already flag destructiveHint=true, the description adds meaningful specifics: 'irreversible — data removed or overwritten by this call cannot be recovered through the API.' It also discloses the dry_run preview behavior and the error-flagged result for previews, which is not covered by annotations. No contradiction with annotations (idempotentHint and destructiveHint are compatible).

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 compact and front-loaded: the primary action and differentiation come first, followed by irreversibility, then the dry_run tip. Every sentence adds value; there is no filler. Structure is efficient for an agent scanning for purpose and safety.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 3-parameter tool with a nested requestBody and no output schema, the description covers essential context: what it deletes, cardinality, alternative for single items, irreversibility, and a dry_run preview mechanism. Nothing required for correct invocation is missing, and the error-flagged preview behavior is explained.

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% — the schema already fully describes projectId, requestBody, and dry_run. The description's mention of 'full collection or a batch' and the dry_run tip adds usage context but not parameter-specific semantics beyond what the schema provides. Baseline of 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?

The description opens with a clear verb+resource statement: 'Deletes a list of Collections.' It immediately differentiates from the sibling `deleteCollection` by specifying cardinality ('targets the full collection or a batch') and explicitly directing single-item use to `deleteCollection`. Purpose is unmistakable.

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 explicitly states when to use this tool versus alternatives: 'For a single item by ID, use `deleteCollection` instead.' It also provides a concrete usage tip (set `dry_run: true` to preview) and explains the preview's error-flag behavior. Usage conditions and exclusions are fully specified.

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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