Add-on scanner for the best target-book plays with supportive sharp movement. Queries /screen across leagues/markets, hydrates odds history, and only treats non-target sharp-book movement as support. Generic market names are auto-resolved per league (e.g. NHL Total → Total Goals, MLB Spread → Run...
AI agents call sharp_plays 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.
The tool scans and queries odds/market data and hydrates history for display; it is a read/analysis tool. Severity is medium because it surfaces sharp betting movement intelligence that could influence financial decisions, but the tool itself does not place bets or move money.
From the tool's definition 'scanner', 'Queries /screen across leagues/markets, hydrates odds history' — retrieves and queries data about sharp movement and odds; no write/execute/destructive actions mentioned
Attacks that exploit this kind of access
Add-on scanner for the best target-book plays with supportive sharp movement. Queries /screen across leagues/markets, hydrates odds history, and only treats non-target sharp-book movement as support. Generic market names are auto-resolved per league (e.g. NHL Total → Total Goals, MLB Spread → Run Line). Each row includes. 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 sharp_plays: 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.
sharp_plays 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 sharp_plays 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 sharp_plays. 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.
sharp_plays 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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