AI agents invoke shell_script to trigger actions in Mcpx. 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 'shell_script' combined with the server's explicit purpose of 'complete shell and SSH mastery' and 'command execution' makes it highly likely this tool runs arbitrary shell scripts.
From the tool's definition Tool name 'shell_script' on a server described as enabling 'command execution, interactive sessions, file transfer, and port forwarding'. Sibling tools include 'shell_exec' and 'shell_spawn', strongly indicating this tool executes shell scripts.
Attacks that exploit this kind of access
shell_script. It is categorised as a Execute tool in the Mcpx MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcpx MCP server in PolicyLayer and add a rule for shell_script: 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 Mcpx. Nothing to install.
shell_script 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 shell_script 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 shell_script. 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.
shell_script is provided by the Mcpx MCP server (rmednitzer/relay-shell). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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