AI agents invoke run_block to trigger actions in Pl. 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.
The tool executes computational blocks within Platforma Desktop, potentially with side effects depending on what those blocks contain. Without knowing block contents, the worst-case scenario is arbitrary execution (similar to Execute category).
From the tool's definition Tool explicitly performs 'run a block' which triggers execution. Sibling tools include 'execute_js' and 'click', indicating this server controls application automation and script execution.
Attacks that exploit this kind of access
Run a block. Stale upstream blocks are started automatically. It is categorised as a Execute tool in the Pl MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Pl MCP server in PolicyLayer and add a rule for run_block: 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 Pl. Nothing to install.
run_block 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_block 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_block. 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_block is provided by the Pl MCP server (@milaboratories/pl-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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