Get historical events that happened on today's date (month and day).
AI agents call today_in_history to retrieve information from Timepoint MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and returns historical information based on a date filter. It performs a query operation with no capability to modify, delete, or execute code. The temporal knowledge platform is being searched for existing data, making this a straightforward Read operation with minimal risk even if misused by an AI agent.
From the tool's definition Tool name 'today_in_history' and description 'Get historical events that happened on today's date' indicate a retrieval operation. The verb 'Get' and the read-only nature of querying historical events confirm no data modification or side effects.
Attacks that exploit this kind of access
Get historical events that happened on today's date (month and day). It is categorised as a Read tool in the Timepoint MCP MCP Server, which means it retrieves data without modifying state.
Register the Timepoint MCP server in PolicyLayer and add a rule for today_in_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 Timepoint MCP. Nothing to install.
today_in_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 today_in_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 today_in_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.
today_in_history is provided by the Timepoint MCP server (timepointai/timepoint-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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