Get 2-3 sample +EV (positive expected value) betting opportunities that represent the quality of edges SharpEdge AI finds. Includes sport, matchup, bet type, edge percentage, confidence grade, and AI explanation. These are representative samples, not live odds.
AI agents call get_sample_edges to retrieve information from SharpEdge MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only retrieves and displays static sample data representing betting opportunities. It does not place bets, move money, or execute any transactions. It is purely informational/read-only content showing example edges for educational or discovery purposes. While it relates to sports betting, it does not commit any financial obligations itself.
From the tool's definition Get 2-3 sample +EV (positive expected value) betting opportunities... These are representative samples, not live odds.
Attacks that exploit this kind of access
Get 2-3 sample +EV (positive expected value) betting opportunities that represent the quality of edges SharpEdge AI finds. Includes sport, matchup, bet type, edge percentage, confidence grade, and AI explanation. These are representative samples, not live odds. It is categorised as a Read tool in the SharpEdge MCP Server MCP Server, which means it retrieves data without modifying state.
Register the SharpEdge MCP Server MCP server in PolicyLayer and add a rule for get_sample_edges: 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 SharpEdge MCP Server. Nothing to install.
get_sample_edges 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_sample_edges 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_sample_edges. 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_sample_edges is provided by the SharpEdge MCP Server MCP server (therealjlc1/sharpedge-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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