run_test_suite
Trigger all test cases in a suite to run asynchronously. Accepts suiteUuid directly, or suiteName + project identifier. Optional: targetUrl to override the default test target. Returns {suiteUuid, runStatus, testsTriggered, note}. Use get_test_suite_results to poll for results.
This record as markdown: /tools/debugg-ai-debugg-ai-mcp/run-test-suite.md
What run_test_suite does on Debugg AI MCP
AI agents invoke run_test_suite to trigger actions in Debugg AI MCP. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why run_test_suite is rated High
This tool executes test cases whose effects depend on configuration arguments (suiteUuid, project identifier, targetUrl). While test execution is typically benign, the ability to redirect tests to arbitrary targetUrls and trigger multiple test cases asynchronously creates a risk of unintended side effects or resource consumption if misused by an AI agent.
From the tool's definition Tool description states it will 'Trigger all test cases in a suite to run asynchronously' and 'Returns {suiteUuid, runStatus, testsTriggered, note}'. The term 'Trigger' combined with 'run asynchronously' indicates execution of external operations (test cases).
Attacks that exploit this kind of access
The rule that runs run_test_suite safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Debugg AI MCP, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_test_suite, this is the rule to start with:
run_test_suite stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Debugg AI MCP, apply this rule, and every run_test_suite call is checked against it from then on.
Questions about run_test_suite
Trigger all test cases in a suite to run asynchronously. Accepts suiteUuid directly, or suiteName + project identifier. Optional: targetUrl to override the default test target. Returns {suiteUuid, runStatus, testsTriggered, note}. Use get_test_suite_results to poll for results. It is categorised as a Execute tool in the Debugg AI MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Debugg AI MCP server in PolicyLayer and add a rule for run_test_suite: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Debugg AI MCP. Nothing to install.
run_test_suite is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_test_suite rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for run_test_suite. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
run_test_suite is provided by the Debugg AI MCP server (debugg-ai/debugg-ai-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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