AI agents invoke solve_visual_challenge to trigger actions in Mk Qa Master. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
The tool name implies active execution of a challenge-solving process, likely involving browser or screen interaction. Given the server's purpose of driving QA end-to-end including web DOM probing and mobile screen analysis, this tool likely executes automated interactions. The description is truncated so confidence is reduced, but the most severe applicable category given the context is Execute.
From the tool's definition 'Apply the AI client' — the description is truncated/uninformative, but the tool name 'solve_visual_challenge' combined with the server context (driving QA loop, browser/DOM probing, Maestro screen analysis) suggests it executes actions to solve visual…
Documented attack patterns abuse exactly the kind of access solve_visual_challenge gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mk Qa Master, and nothing reaches the server without passing your rules. This is the rule we recommend for solve_visual_challenge:
{
"version": "1",
"default": "deny",
"tools": {
"solve_visual_challenge": {
"limits": [
{
"counter": "solve_visual_challenge_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}solve_visual_challenge stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Apply the AI client. It is categorised as a Execute tool in the Mk Qa Master MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mk Qa Master MCP server in PolicyLayer and add a rule for solve_visual_challenge: 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 Mk Qa Master. Nothing to install.
solve_visual_challenge is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the solve_visual_challenge 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 solve_visual_challenge. 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.
solve_visual_challenge is provided by the Mk Qa Master MCP server (kao273183/mk-qa-master). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mk Qa Master, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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22 Mk Qa Master tools catalogued and risk-classified — across an index of 43,000+ MCP servers.