AI agents invoke run to trigger actions in Lint. 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 scripts or files, which can have wide-ranging side effects depending on the script content and runtime environment. This is Execute rather than Read (has side effects) or Write (effects are not necessarily reversible and extend beyond data modification).
From the tool's definition 'Runs a script or file with' indicates arbitrary script execution; combined with sibling tools like ansible-playbook, api, apply, this server appears execution-focused.
Documented attack patterns abuse exactly the kind of access run gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Lint, and nothing reaches the server without passing your rules. This is the rule we recommend for run:
{
"version": "1",
"default": "deny",
"tools": {
"run": {
"limits": [
{
"counter": "run_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}run 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 a script or file with. It is categorised as a Execute tool in the Lint MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Lint MCP server in PolicyLayer and add a rule for run: 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 Lint. Nothing to install.
run 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 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. 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 is provided by the Lint 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 Lint, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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202 Lint tools catalogued and risk-classified — across an index of 43,000+ MCP servers.