Run pre-built named sequences for this project. ALWAYS check project(action="get_status") first - its 'flows' field lists what's available. If a flow matches the user's request, run it via flow(action="run", flowName="...") instead of composing the sequence by hand. Config reloads on every call -...
Risk signalsBulk/mass operation — affects multiple targets
Part of the Ue server.
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AI agents invoke flow to trigger processes or run actions in Ue. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
flow can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"flow": {
"limits": [
{
"counter": "flow_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Ue policy for all 22 tools.
These attack patterns abuse exactly the kind of access flow gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Run pre-built named sequences for this project. ALWAYS check project(action="get_status") first - its 'flows' field lists what's available. If a flow matches the user's request, run it via flow(action="run", flowName="...") instead of composing the sequence by hand. Config reloads on every call - no restart needed. Actions: - run: Execute a flow. Params: flowName, skip?, params?, rollback_on_failure? - plan: Show execution plan without running. Params: flowName - list: List available flows Step types supported in YAML flows: any MCP action (category.action), nested flows (flow:), and 'shell' for running shell/exec commands. Example shell step: steps: 1: { task: shell, options: { command: "npm run up:build" } } params: Runtime options merged into every step's options (highest priority). Use to override YAML-hardcoded values like levelPath, directory, configuration, etc. rollback_on_failure: When true, rollback records from completed steps are invoked in reverse order if a subsequent step fails.. It is categorised as a Execute tool in the Ue MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ue MCP server in PolicyLayer and add a rule for flow: 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 Ue. Nothing to install.
flow 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 flow 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 flow. 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.
flow is provided by the Ue MCP server (ue-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 22 Ue tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.