AI agents invoke cluster_network to trigger actions in PyPSA MCP. 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 name 'cluster_network' in a PyPSA energy modeling context strongly suggests executing a network clustering/aggregation algorithm, which transforms the model structure. This is an Execute-level operation as it runs a computational process that modifies the model. Severity is high because misuse could corrupt the energy model structure. Confidence is low due to the empty description.
From the tool's definition Tool name 'cluster_network' with empty description. Based on the server context (PyPSA energy system modeling), clustering a network implies running a computational algorithm to aggregate/reduce network topology.
Documented attack patterns abuse exactly the kind of access cluster_network 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 cluster_network:
{
"version": "1",
"default": "deny",
"tools": {
"cluster_network": {
"limits": [
{
"counter": "cluster_network_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}cluster_network 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.
Free to start. No card required.
cluster_network. It is categorised as a Execute tool in the PyPSA MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the PyPSA MCP server in PolicyLayer and add a rule for cluster_network: 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.
cluster_network 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 cluster_network 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 cluster_network. 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.
cluster_network 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.