AI agents call odds_prematch to retrieve information from Bet without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and presents pre-match betting odds (1X2, Over/Under 2.5, BTTS markets) from bookmakers. It performs a read-only query operation that normalizes odds data for presentation. There is no indication of fund transfers, data modification, or irreversible operations.
From the tool's definition Tool name 'odds_prematch' and description 'Quote pre-match...normalizzate con lista bookmaker' indicates retrieval and display of pre-match betting odds data from bookmakers.
Attacks that exploit this kind of access
Quote pre-match (1X2, Over/Under 2.5, BTTS) normalizzate con lista bookmaker. It is categorised as a Read tool in the Bet MCP Server, which means it retrieves data without modifying state.
Register the Bet MCP server in PolicyLayer and add a rule for odds_prematch: 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 Bet. Nothing to install.
odds_prematch 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 odds_prematch 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 odds_prematch. 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.
odds_prematch is provided by the Bet MCP server (valerio357/bet_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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