AI agents invoke gradle-build to trigger actions in Http. 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 triggers external build processes whose effects depend on the Gradle configuration and project code. Build systems can execute arbitrary scripts, download dependencies, compile code, run tests, and potentially invoke side effects. This is Execute-category because it runs code/commands whose consequences are determined by project configuration rather than simple data retrieval.
From the tool's definition Tool name 'gradle-build' combined with context of 'Runs' indicates execution of build commands. Gradle is a build automation tool that compiles, tests, and packages code.
Documented attack patterns abuse exactly the kind of access gradle-build gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Http, and nothing reaches the server without passing your rules. This is the rule we recommend for gradle-build:
{
"version": "1",
"default": "deny",
"tools": {
"gradle-build": {
"limits": [
{
"counter": "gradle-build_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}gradle-build 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. It is categorised as a Execute tool in the Http MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Http MCP server in PolicyLayer and add a rule for gradle-build: 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 Http. Nothing to install.
gradle-build 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 gradle-build 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-build. 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-build is provided by the Http MCP server (@paretools/http). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Http, 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 Http tools catalogued and risk-classified — across an index of 43,000+ MCP servers.