staking_plan

Given a bankroll and optional play filter, return stake allocations across recommended bets. Uses fractional Kelly staking: TIER 1 = 2%, TIER 2 = 1% of bankroll. Generic market names (e.g.

Server PropProfessor MCP j17drake/propprofessor-mcp
Category Financial
Risk class Critical
Parameters 00 required

What staking_plan does on PropProfessor MCP

AI agents use staking_plan to commit financial operations through PropProfessor MCP — usually the final step of a payment, billing, or trading workflow. A call moves real money.

Why staking_plan needs a policy

This tool calculates and recommends how much money to stake on bets given a bankroll, directly involving financial commitments on gambling/sports betting markets. While it may only return recommendations rather than executing actual wagers, it is fundamentally a financial planning tool that drives betting decisions with real monetary stakes.

From the tool's definition 'return stake allocations across recommended bets', 'fractional Kelly staking: TIER 1 = 2%, TIER 2 = 1% of bankroll'

Questions about staking_plan

What does the staking_plan tool do? +

Given a bankroll and optional play filter, return stake allocations across recommended bets. Uses fractional Kelly staking: TIER 1 = 2%, TIER 2 = 1% of bankroll. Generic market names (e.g. It is categorised as a Financial tool in the PropProfessor MCP MCP Server, which means it involves financial transactions. Block by default and require explicit approval.

How do I enforce a policy on staking_plan? +

Register the PropProfessor MCP server in PolicyLayer and add a rule for staking_plan: 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.

What risk level is staking_plan? +

staking_plan is a Financial tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit staking_plan? +

Yes. Add a rate_limit block to the staking_plan 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.

How do I block staking_plan completely? +

Set action: deny in the PolicyLayer policy for staking_plan. 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.

What MCP server provides staking_plan? +

staking_plan 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.

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