Execute multiple browser actions sequentially in a single MCP call. Eliminates round-trip overhead for humanization sequences (e.g. Bezier mouse paths, typed text with delays). Each action can have an optional delayAfter (ms) to pause between steps. Returns a single result with the outcome of eac...
High parameter count (12 properties)
Part of the Leapfrog MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents invoke batch_actions to trigger processes or run actions in Leapfrog. 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.
batch_actions can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept 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.
tools:
batch_actions:
rules:
- action: allow
rate_limit:
max: 10
window: 60
validate:
required_args: trueSee the full Leapfrog policy for all 37 tools.
Agents calling execute-class tools like batch_actions have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
batch_actions is one of the high-risk operations in Leapfrog. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.
Execute multiple browser actions sequentially in a single MCP call. Eliminates round-trip overhead for humanization sequences (e.g. Bezier mouse paths, typed text with delays). Each action can have an optional delayAfter (ms) to pause between steps. Returns a single result with the outcome of each action.. It is categorised as a Execute tool in the Leapfrog MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Add a rule in your Intercept YAML policy under the tools section for batch_actions. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Leapfrog MCP server.
batch_actions 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 batch_actions rule in your Intercept 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 Intercept policy for batch_actions. 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.
batch_actions is provided by the Leapfrog MCP server (leapfrog-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept