AI agents use configure_time to create or update resources in PyPSA MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your PyPSA MCP environment.
Without explicit description, classification relies on naming convention and context. 'Configure' indicates a setting modification action, which is reversible and creates/modifies model state (Write category). Severity is medium because misconfiguration of time parameters in energy models could lead to incorrect analyses or model failures, but effects are typically reversible via reconfiguration.
From the tool's definition Tool name 'configure_time' indicates modification of temporal settings in an energy system model. No description provided, but the name and context of sibling tools (add_bus, add_component, add_generator, etc.) suggest this configures model parameters rather…
Documented attack patterns abuse exactly the kind of access configure_time gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and PyPSA MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for configure_time:
{
"version": "1",
"default": "deny",
"tools": {
"configure_time": {
"limits": [
{
"counter": "configure_time_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}configure_time stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
configure_time. It is categorised as a Write tool in the PyPSA MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the PyPSA MCP server in PolicyLayer and add a rule for configure_time: 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 PyPSA MCP. Nothing to install.
configure_time is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the configure_time 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_time. 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_time is provided by the PyPSA MCP server (open-energy-transition/pypsa-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 PyPSA MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
22 PyPSA MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.