This record as markdown: /tools/a2a-cloud/build.md
What build does on A2a Cloud
AI agents invoke build to trigger actions in A2a Cloud. 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 build is rated High
The 'build' tool in an 'Autonomous LLM build orchestrator' context clearly executes build operations (compilation, testing, linting, type-checking) that can run arbitrary code and external operations. While the description is empty, the server's purpose and sibling tools provide strong contextual evidence.
From the tool's definition Tool named 'build' with empty description; sibling tools 'run', 'scan', 'status', and server description mentioning 'plans a goal into tasks, edits code with anchored SEARCH/REPLACE, and verifies every change through build/test/lint/typecheck gates' indicate…
Attacks that exploit this kind of access
The rule that runs build safely
PolicyLayer is an MCP gateway: it sits between your AI agents and A2a Cloud, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For build, this is the rule to start with:
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.
The button opens the PolicyLayer dashboard: create your workspace, connect A2a Cloud, apply this rule, and every build call is checked against it from then on.
Questions about build
build is a execute tool on the A2a Cloud MCP server. It is categorised as a Execute tool in the A2a Cloud MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the A2a Cloud MCP server in PolicyLayer and add a rule for 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 A2a Cloud. Nothing to install.
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 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 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.
build is provided by the A2a Cloud MCP server (robGetsTheJobDone/a2a-cloud). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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