Shows the Gradle dependency tree with structured output per configuration.
AI agents call gradle-dependencies to retrieve information from Make without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and displays dependency information from a Gradle project. It has no side effects—it does not execute code, modify configuration, delete anything, or commit any resources. It is purely informational, making it a Read operation with low severity since the information exposed is typically already available to developers with project access.
From the tool's definition Tool name is 'gradle-dependencies' and description states it 'Shows the Gradle dependency tree with structured output per configuration.' The verb 'Shows' indicates retrieval and presentation of dependency information without any modification, creation, or…
Documented attack patterns abuse exactly the kind of access gradle-dependencies 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 gradle-dependencies:
{
"version": "1",
"default": "deny",
"tools": {
"gradle-dependencies": {}
}
} gradle-dependencies is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Shows the Gradle dependency tree with structured output per configuration. It is categorised as a Read tool in the Make MCP Server, which means it retrieves data without modifying state.
Register the Make MCP server in PolicyLayer and add a rule for gradle-dependencies: 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.
gradle-dependencies is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the gradle-dependencies 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 gradle-dependencies. 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.
gradle-dependencies 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.
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