This record as markdown: /tools/agentics-ai-code-mcp/run-command.md
What run_command does on Code MCP Server
AI agents invoke run_command to trigger actions in Code MCP 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.
Why run_command is rated High
Shell command execution is a critical capability that can trigger external operations, system calls, and code execution with effects entirely dependent on the command arguments. An AI agent given this tool without strict guardrails could execute destructive commands (rm -rf), exfiltrate data, or compromise system security.
From the tool's definition Tool name 'run_command' with description 'Execute a shell command' explicitly indicates execution of arbitrary shell commands.
Attacks that exploit this kind of access
The rule that runs run_command safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Code MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_command, this is the rule to start with:
run_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.
The button opens the PolicyLayer dashboard: create your workspace, connect Code MCP Server, apply this rule, and every run_command call is checked against it from then on.
Questions about run_command
Execute a shell command. It is categorised as a Execute tool in the Code MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Code MCP Server MCP server in PolicyLayer and add a rule for run_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 Code MCP Server. Nothing to install.
run_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 run_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 run_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.
run_command is provided by the Code MCP Server MCP server (agentics-ai/code-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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