AI agents use create_result to create or update resources in QASE MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your QASE MCP Server environment.
This tool creates a new test run result record in Qase, which is a data creation operation. It is reversible (results can be deleted or modified), so it does not qualify as Destructive. It does not execute arbitrary code or trigger external operations beyond the expected API operation, so Execute does not apply. The classification is Write: creates data reversibly.
From the tool's definition Tool name 'create_result' and description 'Create test run result' indicate the tool creates/writes new data (a test result record) in the Qase platform. The name and description align with Write category operations that create new entities reversibly.
Documented attack patterns abuse exactly the kind of access create_result gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and QASE MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for create_result:
{
"version": "1",
"default": "deny",
"tools": {
"create_result": {
"limits": [
{
"counter": "create_result_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}create_result stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Create test run result. It is categorised as a Write tool in the QASE MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the QASE MCP Server MCP server in PolicyLayer and add a rule for create_result: 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 QASE MCP Server. Nothing to install.
create_result is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the create_result 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 create_result. 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.
create_result is provided by the QASE MCP Server MCP server (rikuson/mcp-qase). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from QASE MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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26 QASE MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.