PlanRadar’s QA team built a custom MCP integration that connects Claude Code directly to Tuskr’s API, turning their test case management system into the foundation of a fully traceable, AI-assisted QA workflow.
PlanRadar at a Glance
MagdalenaGerle PlanRadar is a leading digital SaaS platform for documentation, communication and reporting in construction, facility management and real estate projects. It enables customers to work more efficiently, enhance quality and achieve full project transparency. Today, PlanRadar serves more than 200,000 users across 75+ countries.
That scale makes QA high-stakes. Mazen Galal, the Software Testing Engineer responsible for PlanRadar’s regression library and automation pipeline, needed a test management tool he could not just use, but build on.
The QA Challenge: Scaling Test Case Coverage Without Losing Hours to Manual Work
When writing test coverage for every Jira ticket takes hours, speed becomes a QA problem.
PlanRadar’s QA team was already using Tuskr when Mazen joined. The tool had been in place for years. But Mazen needed more from it: a way to scale test authoring with AI assistance, keep automation cases in sync with manual ones, and stay connected to Jira without the whole workflow becoming a patchwork of tabs and copy-paste.
The core problem was time. Drafting structured test cases from scratch for every new feature ticket, then keeping those cases traceable back to the original story or bug report, took hours. As PlanRadar’s product grew, that pace wasn’t going to hold.
“I wanted AI-assisted test authoring without losing Tuskr as the source of truth,” Mazen said. “The MCP closes that loop.”
What PlanRadar Needed from a Test Case Management Tool
Seven requirements. Every one of them non-negotiable.
Mazen’s evaluation list was specific. Each item mapped directly to a workflow need.
An open, well-documented REST API. Non-negotiable. This is what made building automation around the tool possible at all. Without it, the whole pipeline Mazen had in mind would not work.
Clean suite and section organization for a large regression library. A growing test suite needs structure that scales without becoming a navigation problem. Flat lists and unlabeled folders don’t cut it at this volume.
First-class test run management with clear pass, fail, and blocked states. Not a workaround. Not a tag system stretched beyond its purpose. Proper run tracking with full history.
Jira traceability. Linking test cases directly back to stories and tickets is how PlanRadar’s dev and QA teams stay aligned. Without this, coverage has gaps no one can see.
Custom fields. PlanRadar tracks automation status and priority at the test case level. If a tool doesn’t support custom fields, that data lives in a spreadsheet somewhere, which means it’s already out of date.
Fast, uncluttered UX. Minimal clicks to create, review, and execute test runs. No feature bloat that turns every daily action into a three-step process.
Sensible pricing for a growing QA team. A tool that prices teams out as they scale is not a long-term solution.
Tuskr met all seven. The API, in particular, is what made PlanRadar’s most ambitious use of the tool possible.
How Tuskr’s Open API Powers PlanRadar’s AI-Assisted Test Authoring Workflow
Mazen didn’t just adopt Tuskr. He built on top of it.
The centerpiece of PlanRadar’s QA setup is a custom Tuskr MCP server, Model Context Protocol, that lets Claude, Anthropic’s AI assistant running inside Claude Code, talk directly to Tuskr’s API. It reads, creates, and updates suites, sections, and test cases, without Mazen having to copy-paste between tools.
The Tuskr and Claude Code workflow, step by step
The process starts with a Jira ticket. Claude drafts a structured test plan. Mazen reviews it. Claude then generates the automated specs in Capybara or Playwright using a page-object style. The cases stay synced inside Tuskr the whole way through.
“The Tuskr API being clean and predictable is what made the whole integration possible,” Mazen said. “That was the deciding factor in building on top of it rather than fighting it.”
— Mazen Galal
Today, PlanRadar’s QA team manages 7,656 test cases across 12 projects, with 11 custom fields keeping automation status and priority consistent across the library. At any point, Mazen can see exactly what’s covered by automation and what still runs manually, with no cross-referencing required.
The Results: Centralized Test Cases, Full Automation Traceability, and a QA Process That Scales
One source of truth changed how the whole team works.
The practical changes since Mazen built the MCP integration are concrete.
Gaps in test coverage are now visible rather than buried in a spreadsheet tab no one opened. New team members find the authoritative test case list immediately. Reviews happen against shared cases, not emailed files. And automation traceability is built into the workflow, not added after the fact.
The part that mattered most to Mazen: drafting test coverage for a new ticket used to take hours. With the AI-assisted pipeline running through Tuskr, that time has come down significantly. <span
“The open API above all,” Mazen said. “It’s what let me wire Tuskr into an AI-assisted automation pipeline that simply wouldn’t be possible with a closed tool.”
— Mazen Galal
PlanRadar’s team has run Tuskr for 4.6 years. It started as a place to document test cases and track runs. It’s now the backbone of a QA pipeline that connects Jira, Claude, and automated specs into one traceable system.
Build a Scalable QA Pipeline with Tuskr
Whether your team is managing hundreds of test cases or thousands, Tuskr gives you the structure, the open API, and the flexibility to build a QA workflow that actually grows with you.
