View your logged betting history. Filter by status (pending/won/lost/push/all), league, recency, and limit. Returns most recent first.
AI agents call get_pick_history to retrieve information from PropProfessor 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 queries historical betting records with various filter parameters. It has no side effects, does not modify data, execute code, delete records, or involve financial transactions. It is purely a data retrieval/query operation against logged history, making it a Read category tool with low severity since viewing one's own historical bets presents minimal risk even if misused by an AI agent.
From the tool's definition Tool description states 'View your logged betting history' with filtering options (status, league, recency, limit) and indicates it 'Returns most recent first.' The verb 'View' and action of retrieving historical data without modification are characteristic…
Attacks that exploit this kind of access
View your logged betting history. Filter by status (pending/won/lost/push/all), league, recency, and limit. Returns most recent first. It is categorised as a Read tool in the PropProfessor MCP MCP Server, which means it retrieves data without modifying state.
Register the PropProfessor MCP server in PolicyLayer and add a rule for get_pick_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 PropProfessor MCP. Nothing to install.
get_pick_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_pick_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_pick_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_pick_history is provided by the PropProfessor MCP server (j17drake/propprofessor-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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