AI agents invoke run_pascal to trigger actions in Claude Pascal MCP Server. 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.
This tool executes Pascal/Delphi code on local or remote (Android) systems. While the tool description is empty, the server's explicit purpose and sibling ADB tools establish that run_pascal triggers code execution with side effects dependent on the Pascal program's arguments and logic. This falls under Execute rather than Write because it runs compiled programs/scripts rather than merely storing data.
From the tool's definition Tool name 'run_pascal' combined with server description stating it 'compile[s], run[s], and interact[s] with Pascal/Delphi desktop applications' and 'GUI automation' indicates execution of arbitrary code.
Documented attack patterns abuse exactly the kind of access run_pascal gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Claude Pascal MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for run_pascal:
{
"version": "1",
"default": "deny",
"tools": {
"run_pascal": {
"limits": [
{
"counter": "run_pascal_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
} run_pascal 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.
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run_pascal. It is categorised as a Execute tool in the Claude Pascal MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Claude Pascal MCP Server MCP server in PolicyLayer and add a rule for run_pascal: 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 Claude Pascal MCP Server. Nothing to install.
run_pascal 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_pascal 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_pascal. 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_pascal is provided by the Claude Pascal MCP Server MCP server (tina4stack/claude-pascal-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Claude Pascal MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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53 Claude Pascal MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.