AI agents invoke analyze_incident to trigger actions in PilotOps 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 description is empty, so classification relies on the tool name and server context. 'analyze_incident' likely orchestrates multiple sub-operations (querying metrics, logs, alerts) and may trigger automated responses or runbook generation.
From the tool's definition Tool name 'analyze_incident' on a server designed for 'AI-driven incident response' with tools spanning read, write, and execute operations across Prometheus, Grafana, Loki, PagerDuty, and Slack.
Documented attack patterns abuse exactly the kind of access analyze_incident gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and PilotOps MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for analyze_incident:
{
"version": "1",
"default": "deny",
"tools": {
"analyze_incident": {
"limits": [
{
"counter": "analyze_incident_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}analyze_incident 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.
Free to start. No card required.
analyze_incident. It is categorised as a Execute tool in the PilotOps MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the PilotOps MCP server in PolicyLayer and add a rule for analyze_incident: 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 PilotOps MCP. Nothing to install.
analyze_incident 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 analyze_incident 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 analyze_incident. 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.
analyze_incident is provided by the PilotOps MCP server (muhammedehab35/pilot_ops-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from PilotOps MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
12 PilotOps MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.