AI agents call get_result to retrieve information from QASE MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This is a read-only query operation that retrieves test run result information from the Qase platform. It has no side effects, does not modify data, and does not trigger external operations beyond fetching existing records. The blast radius of misuse is minimal—an attacker could view test results they may not have authorization for, but cannot alter or delete data.
From the tool's definition Tool name 'get_result' and description 'Get test run result by code and hash' indicate a retrieval operation with parameters (code, hash) that fetches existing test data without modification.
Documented attack patterns abuse exactly the kind of access get_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 get_result:
{
"version": "1",
"default": "deny",
"tools": {
"get_result": {}
}
}get_result is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get test run result by code and hash. It is categorised as a Read tool in the QASE MCP Server MCP Server, which means it retrieves data without modifying state.
Register the QASE MCP Server MCP server in PolicyLayer and add a rule for get_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.
get_result is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_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 get_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.
get_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.