plan_journey
AI agents call plan_journey to retrieve information from GovUK MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Journey planning is a read/query operation that retrieves route and transport information without side effects. The server context (transport, business, healthcare data) and the tool name strongly suggest this is a query tool. Empty description lowers confidence slightly, but no evidence of write, execute, or destructive behavior.
From the tool's definition Tool name 'plan_journey' on a UK government data server covering transport services; description is empty.
Attacks that exploit this kind of access
plan_journey. It is categorised as a Read tool in the GovUK MCP Server MCP Server, which means it retrieves data without modifying state.
Register the GovUK MCP Server MCP server in PolicyLayer and add a rule for plan_journey: 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 GovUK MCP Server. Nothing to install.
plan_journey 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 plan_journey 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 plan_journey. 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.
plan_journey is provided by the GovUK MCP Server MCP server (stealth-labs-ltd/govuk-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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