AI agents invoke diagnose_error to trigger actions in slurm_MCP. 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 server description explicitly mentions 'error diagnosis' as a capability. On HPC clusters, diagnosing errors typically involves running diagnostic commands, inspecting logs, or executing queries via SSH on the remote cluster. Since the description is empty, confidence is lowered, but the most likely behavior involves executing commands on a remote system to gather diagnostic information.
From the tool's definition Tool name 'diagnose_error' on a server that 'Enables interaction with Slurm HPC clusters via SSH, allowing job submission, monitoring, and error diagnosis through MCP clients'. Description is empty.
Documented attack patterns abuse exactly the kind of access diagnose_error gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and slurm_MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for diagnose_error:
{
"version": "1",
"default": "deny",
"tools": {
"diagnose_error": {
"limits": [
{
"counter": "diagnose_error_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}diagnose_error 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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diagnose_error. It is categorised as a Execute tool in the slurm_MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the slurm_ MCP server in PolicyLayer and add a rule for diagnose_error: 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 slurm_MCP. Nothing to install.
diagnose_error 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 diagnose_error 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 diagnose_error. 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.
diagnose_error is provided by the slurm_ MCP server (pengc0066-star/slurm_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from slurm_MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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5 slurm_MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.