AI agents call get_run to retrieve information from TestRail MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The 'get_run' tool retrieves test run data from TestRail without modification. Although the description is empty, the naming convention and context of sibling operations (add_*, delete_*, close_*) strongly indicate this is a read-only query operation. Low severity because retrieving test run metadata poses minimal risk even if misused by an agent.
From the tool's definition Tool name is 'get_run', which follows standard REST/API conventions for read operations (get_ prefix indicates retrieval). Context shows sibling tools with clear write (add_*), destructive (delete_*), and close (close_run) operations.
Documented attack patterns abuse exactly the kind of access get_run gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and TestRail MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_run:
{
"version": "1",
"default": "deny",
"tools": {
"get_run": {}
}
}get_run is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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get_run. It is categorised as a Read tool in the TestRail MCP Server MCP Server, which means it retrieves data without modifying state.
Register the TestRail MCP Server MCP server in PolicyLayer and add a rule for get_run: 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 TestRail MCP Server. Nothing to install.
get_run 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_run 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_run. 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_run is provided by the TestRail MCP Server MCP server (sker65/testrail-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from TestRail 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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29 TestRail MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.