Run make depend command to install or update dependencies
AI agents invoke make_depend 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.
This tool executes external commands (make depend) that can install or update system-wide or project dependencies. While nominally for dependency management, execution of arbitrary make targets and dependency installation scripts creates significant risk if an AI agent misconfigures or targets the wrong project.
From the tool's definition Tool description states 'Run make depend command' which directly executes a system command. The make tool system can trigger arbitrary shell operations and dependency installation scripts, whose effects depend on the project's Makefile and dependency…
Documented attack patterns abuse exactly the kind of access make_depend 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 make_depend:
{
"version": "1",
"default": "deny",
"tools": {
"make_depend": {
"limits": [
{
"counter": "make_depend_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} make_depend 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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Run make depend command to install or update dependencies. 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 make_depend: 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.
make_depend 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 make_depend 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 make_depend. 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.
make_depend 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.