Get recent search history.
AI agents call get_history to retrieve information from PyWeatherMCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves previously searched locations from local search history without creating, modifying, deleting, or executing any operations. It is a read-only query operation with minimal security risk—the data returned is non-sensitive location search metadata that the user has already interacted with.
From the tool's definition Tool name 'get_history' and description 'Get recent search history' indicate a retrieval operation with no modifications or side effects.
Attacks that exploit this kind of access
Get recent search history. It is categorised as a Read tool in the PyWeatherMCP MCP Server, which means it retrieves data without modifying state.
Register the PyWeather MCP server in PolicyLayer and add a rule for get_history: 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 PyWeatherMCP. Nothing to install.
get_history 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 get_history 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 get_history. 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.
get_history is provided by the PyWeather MCP server (zerosks471/pyweathermcp). 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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