Execute a command and analyze the result with AI-powered smart suggestions. Provides intelligent recommendations for fixing failures, optimizing workflows, and identifying issues.
AI agents invoke analyze_command to trigger actions in MCP DevTools Server. 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 executes arbitrary commands on the system, which can have wide-ranging side effects depending on what command is passed. The AI-powered analysis layer is secondary; the primary action is command execution. This warrants high severity due to the potential blast radius of executing arbitrary system commands.
From the tool's definition "Execute a command and analyze the result" - the tool explicitly runs commands, with AI-powered analysis of the output
Documented attack patterns abuse exactly the kind of access analyze_command gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP DevTools Server, and nothing reaches the server without passing your rules. This is the rule we recommend for analyze_command:
{
"version": "1",
"default": "deny",
"tools": {
"analyze_command": {
"limits": [
{
"counter": "analyze_command_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}analyze_command 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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Execute a command and analyze the result with AI-powered smart suggestions. Provides intelligent recommendations for fixing failures, optimizing workflows, and identifying issues. It is categorised as a Execute tool in the MCP DevTools Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP DevTools Server MCP server in PolicyLayer and add a rule for analyze_command: 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 MCP DevTools Server. Nothing to install.
analyze_command 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_command 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_command. 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_command is provided by the MCP DevTools Server MCP server (rshade/mcp-devtools-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP DevTools Server, 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.
79 MCP DevTools Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.