Polarion MCP Server

postTestRuns

Create test runs in Polarion with a single API call. Preview the exact request using dry-run mode before committing to avoid duplicates.

Instructions

Creates a list of Test Runs. Effect: creates a new resource on each call — calling it again with the same input creates a duplicate; it is not idempotent. 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

Name	Required	Description
`dry_run`	No	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.
`projectId`	Yes	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.
`requestBody`	Yes	The Test Run(s) body.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.2.0Sep 17, 2026

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."

Changed1 schema field changedv1.1.0Sep 11, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "data": {
+      "items": {
+        "properties": {
+          "id": {
+            "example": "MyProjectId/MyTestRunId",
+            "type": "string"
+          },
+          "links": {
+            "properties": {
+              "portal": {
+                "example": "server-host-name/application-path/polarion/redirect/project/MyProjectId/testrun?id=MyTestRunId&revision=1234",
+                "type": "string"
+              },
+              "self": {
+                "example": "server-host-name/application-path/projects/MyProjectId/testruns/MyTestRunId?revision=1234",
+                "type": "string"
+              }
+            },
+            "type": "object"
+          },
+          "type": {
+            "enum": [
+              "testruns"
+            ],
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "type": "object"
+}

Changed1 schema field changedSep 7, 2026

addedInput schema / properties / dry_run

Added value: +{
+  "description": "If true, validate and return the request that would be sent without calling Polarion.",
+  "type": "boolean"
+}

First observedv1.0.0Jun 13, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already indicate idempotentHint=false, but the description adds the concrete consequence of duplicate creation on repeated calls. It also explains the dry_run preview behavior and the error-flagged result, which is beyond what annotations provide. This adds useful context about side effects and output interpretation.

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 concise at three sentences, front-loads the core purpose, and then adds the effect and a practical tip. No redundant information; each sentence earns its place.

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?

Given the tool's complexity (nested objects, multiple parameters, output schema present), the description is reasonably complete. It covers the non-idempotent effect, the dry_run preview, and the output flag behavior. Prerequisites like projectId are covered in the schema. It does not mention alternatives, but that is handled under usage guidelines.

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 the baseline is 3. The description adds a tip about dry_run, but this is already documented in the schema's parameter description. It does not add further meaning for projectId or requestBody beyond what the schema provides.

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 clearly states the verb 'creates' and the resource 'list of Test Runs', which is distinct from sibling operations like getTestRuns, patchTestRuns, and deleteTestRuns. It also explicitly notes the non-idempotent behavior, making the purpose unambiguous.

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?

The description includes a valuable tip about using dry_run to preview, which guides safe usage. However, it does not explicitly state when to use this tool versus alternatives (e.g., patching or deleting test runs). The purpose is implied by the name, but no explicit exclusions or alternative references are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server