AI agents invoke configure_session to trigger actions in PiloTY. 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.
Given the server context (persistent interactive terminal, shell interactions), configuring a session likely modifies terminal/shell session parameters or behavior. With an empty description, confidence is low, but the Execute category fits best given sibling tools like send_line, send_signal, and send_control that indicate active shell interaction.
From the tool's definition Tool name 'configure_session' on a server providing 'persistent, interactive terminal' capabilities; description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access configure_session gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and PiloTY, and nothing reaches the server without passing your rules. This is the rule we recommend for configure_session:
{
"version": "1",
"default": "deny",
"tools": {
"configure_session": {
"limits": [
{
"counter": "configure_session_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}configure_session 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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configure_session. It is categorised as a Execute tool in the PiloTY MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the PiloTY MCP server in PolicyLayer and add a rule for configure_session: 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 PiloTY. Nothing to install.
configure_session 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 configure_session 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 configure_session. 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.
configure_session is provided by the PiloTY MCP server (yiwenlu66/piloty). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 17 PiloTY tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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17 PiloTY tools catalogued and risk-classified — across an index of 42,500+ MCP servers.