Runs Lerna monorepo commands (list, run, changed, version) and returns structured package information.
AI agents invoke lerna to trigger actions in Make. 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 external commands via Lerna, a monorepo manager. The 'run' subcommand specifically executes npm scripts across packages, which can trigger arbitrary code. The 'version' command modifies package metadata and can trigger git operations and publishing. This is Execute-category because the effects depend on which Lerna commands and scripts the AI agent invokes.
From the tool's definition Tool 'runs Lerna monorepo commands' including 'run', 'version', and others. Lerna's 'run' command executes arbitrary scripts across packages, and 'version' modifies package versions and can trigger publishing workflows.
Documented attack patterns abuse exactly the kind of access lerna gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Make, and nothing reaches the server without passing your rules. This is the rule we recommend for lerna:
{
"version": "1",
"default": "deny",
"tools": {
"lerna": {
"limits": [
{
"counter": "lerna_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}lerna 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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Runs Lerna monorepo commands (list, run, changed, version) and returns structured package information. It is categorised as a Execute tool in the Make MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Make MCP server in PolicyLayer and add a rule for lerna: 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 Make. Nothing to install.
lerna 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 lerna 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 lerna. 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.
lerna is provided by the Make MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Make, 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.
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