[Deprecated] Add a load to a PyPSA model. Use add_component() instead.
AI agents use add_load 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.
Adding a load to an energy system model is a reversible modification that creates new data within the PyPSA model structure. It does not execute arbitrary code, delete data, or cause financial transactions. While marked deprecated, the tool still modifies model state.
From the tool's definition Tool name 'add_load' and description state it 'Add[s] a load to a PyPSA model', which creates a new data entity in the energy system model.
Documented attack patterns abuse exactly the kind of access add_load 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 add_load:
{
"version": "1",
"default": "deny",
"tools": {
"add_load": {
"limits": [
{
"counter": "add_load_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_load 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.
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[Deprecated] Add a load to a PyPSA model. Use add_component() instead. 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 add_load: 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.
add_load 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 add_load 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 add_load. 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.
add_load 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.
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22 PyPSA MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.