AI agents use add_result 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 result data in TestRail (a test management system). It does not delete or overwrite existing results irreversibly, nor execute arbitrary code or move financial resources.
From the tool's definition Tool name 'add_result' combined with sibling tools 'add_bulk_results' and 'add_test_cases_bulk' that push data back to TestRail. The name 'add_result' indicates creation/modification of test result records.
Attacks that exploit this kind of access
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_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 Testrail. Nothing to install.
add_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 add_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 add_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.
add_result 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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