java_gradle
Ejecuta un comando Gradle en el proyecto. Provee los argumentos (ej.
This record as markdown: /tools/inggerman-mcps/java-gradle.md
What java_gradle does on MCP Framework Personal
AI agents invoke java_gradle to trigger actions in MCP Framework Personal. 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.
Why java_gradle is rated High
This tool runs Gradle commands, which can execute arbitrary build scripts, compile code, run tests, deploy artifacts, or trigger plugins. Arbitrary build execution has a high blast radius as it can run code, modify filesystems, or interact with external systems depending on the Gradle tasks invoked.
From the tool's definition "Ejecuta un comando Gradle en el proyecto" (Executes a Gradle command in the project)
Attacks that exploit this kind of access
The rule that runs java_gradle safely
PolicyLayer is an MCP gateway: it sits between your AI agents and MCP Framework Personal, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For java_gradle, this is the rule to start with:
java_gradle 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.
The button opens the PolicyLayer dashboard: create your workspace, connect MCP Framework Personal, apply this rule, and every java_gradle call is checked against it from then on.
Questions about java_gradle
Ejecuta un comando Gradle en el proyecto. Provee los argumentos (ej. It is categorised as a Execute tool in the MCP Framework Personal MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the MCP Framework Personal MCP server in PolicyLayer and add a rule for java_gradle: 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 Framework Personal. Nothing to install.
java_gradle 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 java_gradle 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 java_gradle. 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.
java_gradle is provided by the MCP Framework Personal MCP server (inggerman/mcps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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