Low Risk

hfss_query_modeling_knowledge

Query local HFSS modeling knowledge base for best-practice hints before automatic modeling

How to control hfss_query_modeling_knowledge ↓

What hfss_query_modeling_knowledge does on HFSS MCP Server

AI agents call hfss_query_modeling_knowledge to retrieve information from HFSS MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

Why hfss_query_modeling_knowledge needs a policy

The tool queries a local knowledge base to retrieve best-practice information. This is a read-only operation with no side effects, no code execution, and no data modification. The confidence is high because the description clearly indicates a query/retrieval pattern against static knowledge resources.

From the tool's definition Tool name contains 'query' and description states 'Query local HFSS modeling knowledge base for best-practice hints' — this is a retrieval operation that reads from a local knowledge base without modifying, deleting, or executing external operations.

Documented attack patterns abuse exactly the kind of access hfss_query_modeling_knowledge gives an agent:

How to control hfss_query_modeling_knowledge

PolicyLayer is an MCP gateway — it sits between your AI agents and HFSS MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for hfss_query_modeling_knowledge:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "hfss_query_modeling_knowledge": {}
  }
}

hfss_query_modeling_knowledge is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

  1. Create a free account and register HFSS MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
CAP THIS TOOL →

Free to start. No card required.

Related tools and policies

Go deeper

Questions about hfss_query_modeling_knowledge

What does the hfss_query_modeling_knowledge tool do? +

Query local HFSS modeling knowledge base for best-practice hints before automatic modeling. It is categorised as a Read tool in the HFSS MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on hfss_query_modeling_knowledge? +

Register the HFSS MCP Server MCP server in PolicyLayer and add a rule for hfss_query_modeling_knowledge: 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 HFSS MCP Server. Nothing to install.

What risk level is hfss_query_modeling_knowledge? +

hfss_query_modeling_knowledge is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit hfss_query_modeling_knowledge? +

Yes. Add a rate_limit block to the hfss_query_modeling_knowledge 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.

How do I block hfss_query_modeling_knowledge completely? +

Set action: deny in the PolicyLayer policy for hfss_query_modeling_knowledge. 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.

What MCP server provides hfss_query_modeling_knowledge? +

hfss_query_modeling_knowledge is provided by the HFSS MCP Server MCP server (leonardwy/hfss_mcpserver). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every HFSS MCP Server tool call.

Start from HFSS MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

28 HFSS MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.