A ClickUp-triggered QA workflow where an AI agent reads acceptance criteria, runs browser tests and posts a structured result back to the task.
ClickUpMCPPlaywrightWebhooks
ROLEAutomation Developer
FOCUSTraceable QA from acceptance criteria to test result
CONTEXTIndependent Build · AI QA Automation
PROJECT GALLERY
Inside the project.
Selected QA MCP evidence shows the workflow architecture plus how the agent returns a plan or a completed result to the originating ClickUp task.
3 images
ClickUp QA automation flowArchitecture connecting ClickUp, webhooks, an AI QA agent, MCP tools and Playwright.QA plan returned to ClickUpAn AI-generated test plan requests the missing information needed to proceed safely.QA result returned to ClickUpCompleted browser QA result posted back to the task with PASS evidence.
01 / PROJECT BRIEF
The problem and context.
QA MCP connects a QA event in ClickUp to an automated browser-testing workflow. The aim is to keep the acceptance criteria, the test run and the final QA result attached to the same task instead of spreading the handoff across different tools and conversations.
When a task enters testing, a webhook starts the orchestration flow. The agent reads the task context through ClickUp MCP, uses Playwright MCP for browser validation, then returns a structured PASS or FAIL summary to the original task.
02 / MY CONTRIBUTION
What I owned.
Built the ClickUp webhook-driven orchestration flow.
Connected ClickUp MCP for task context and QA comments.
Used Playwright MCP for browser testing.
Returned structured PASS or FAIL summaries to the task.
03 / WORKFLOW
How the system moves.
01
A task moves into testing
ClickUp triggers the workflow when the task reaches the intended QA stage.
02
Read criteria and test the browser flow
The QA agent reads acceptance criteria, then runs browser checks through Playwright MCP.
03
Write the result back to the task
A PASS or FAIL summary is posted to ClickUp so the test result stays alongside the requirement.
04 / DELIVERED
Concrete outputs.
ClickUp webhook workflow
MCP-connected QA agent
Playwright browser-validation loop
Task-level QA result summary
05 / EVIDENCE
What the captures demonstrate.
A task needs clearer criteria
The plan screenshot records NEEDS INFORMATION when a task provides a URL and a short description without enough business requirements, user steps or acceptance criteria.
Browser output is checked
The result screenshot records a PASS for checking that the requested bird content is displayed on the test website, including the heading and supporting details.
Evidence returns to the task
The completed ClickUp comment includes a check summary and an attached browser screenshot, keeping the reported result alongside the original requirement.
SCOPE & LIMITATIONS
How to read this case study.
These captures demonstrate a plan and a completed content-display check. They are not a benchmark of test coverage, accuracy or time saved, and a reported PASS applies to the checks described in that task rather than the entire product.
OUTCOME
A traceable QA loop that keeps requirements, automated browser validation and the final result connected in the same task workspace.