Simplified local mode query - Best for entity-specific queries. Focuses on finding specific concepts, tools, or entities within your domains.
AI agents call query_local to retrieve information from Knowledge without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves information from a knowledge base without creating, modifying, deleting, or executing any external operations. It is purely a data retrieval mechanism with no side effects, fitting the Read category. The blast radius of misuse is minimal since an AI agent can only retrieve information it is already authorized to access within the knowledge base.
From the tool's definition Tool name 'query_local' and description indicate it 'focuses on finding specific concepts, tools, or entities within your domains' - a retrieval operation with no modification or execution capability.
Documented attack patterns abuse exactly the kind of access query_local gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Knowledge, and nothing reaches the server without passing your rules. This is the rule we recommend for query_local:
{
"version": "1",
"default": "deny",
"tools": {
"query_local": {}
}
}query_local is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Simplified local mode query - Best for entity-specific queries. Focuses on finding specific concepts, tools, or entities within your domains. It is categorised as a Read tool in the Knowledge MCP Server, which means it retrieves data without modifying state.
Register the Knowledge MCP server in PolicyLayer and add a rule for query_local: 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 Knowledge. Nothing to install.
query_local is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the query_local 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 query_local. 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.
query_local is provided by the Knowledge MCP server (olafgeibig/knowledge-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 6 Knowledge tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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6 Knowledge tools catalogued and risk-classified — across an index of 42,500+ MCP servers.