This record as markdown: /tools/synthetic-ai-ae-mcp/run-jsx-json.md
What run_jsx_json does on Ae
AI agents invoke run_jsx_json to trigger actions in Ae. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
timeoutMs | number | — | Process timeout in milliseconds. Defaults to 120000. |
scriptBody | string | Yes | JSX body. Call __write(payload) to return structured data. |
Parameters from the server's own tool schema.
Why run_jsx_json is rated High
run_jsx_json triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs run_jsx_json safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ae, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_jsx_json, this is the rule to start with:
run_jsx_json 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 Ae, apply this rule, and every run_jsx_json call is checked against it from then on.
Questions about run_jsx_json
Run JSX inside the shared JSON wrapper and return the parsed JSON payload. It is categorised as a Execute tool in the Ae MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
run_jsx_json accepts 2 parameters: timeoutMs, scriptBody. Required: scriptBody. The full parameter table on this page comes from the server's own tool schema.
Register the Ae MCP server in PolicyLayer and add a rule for run_jsx_json: 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 Ae. Nothing to install.
run_jsx_json 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_jsx_json 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_jsx_json. 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_jsx_json is provided by the Ae MCP server (@synthetic-ai/ae-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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