AI agents use add_bulk_results to create or update resources in Testrail — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Testrail environment.
This tool creates or modifies test results in TestRail by posting bulk result data. The verb 'Post' and action of adding results to TestRail indicate data modification. It is reversible (results can typically be re-run or updated), so it falls under Write rather than Destructive or Execute.
From the tool's definition Post many results in one TestRail call
Attacks that exploit this kind of access
Post many results in one TestRail call (much faster than looping add_result). It is categorised as a Write tool in the Testrail MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Testrail MCP server in PolicyLayer and add a rule for add_bulk_results: 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. Nothing to install.
add_bulk_results 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 add_bulk_results 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 add_bulk_results. 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.
add_bulk_results is provided by the Testrail MCP server (sergey-bl/testrail-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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