This MCP server has severe definition quality gaps. The single tool 'simulate_roi' has a reasonable name but lacks critical description depth, parameter validation guidance, and output schema documentation. The tool description (97 chars) is minimally adequate but fails to explain WHEN to use this tool, what prerequisites exist, or how it differs from similar pricing/discount tools. Input parameters lack type information in the schema (cart_items is 'list[dict]' with no field-level schema), and the discount_pct parameter has a trivial default (0.0) with no constraint documentation. The output schema is completely undocumented, the tool returns a dict with keys like 'gross_revenue', 'total_cost', 'net_profit', 'profit_margin_pct', 'roi_ratio', but no schema is provided to the MCP client, forcing the LLM to infer field names and types. No error handling guidance exists, what happens if cart_items is empty, malformed, or contains negative values? The code performs no input validation and would silently return division-by-zero protection (max(1.0, total_cost)) without documenting this behavior. Security-wise, the tool accepts arbitrary dict structures without sanitization. The tool is marked READ_ONLY, which is correct, but no tool annotations (readOnlyHint, idempotentHint) are present in the schema. This server appears to be a simple Python SDK wrapper with no actual MCP server implementation visible, the transport is UNKNOWN and no MCP protocol code (request/response handling, tool registration, schema validation) is shown.

• Build a complete MCP server wrapper: implement a server class that registers tools via the MCP protocol, handles tool calls, returns properly structured responses, and exposes this via HTTP/SSE or stdio transport.
• Document the full output schema in the tool definition. Specify that the response is a JSON object with fields: gross_revenue (float), total_cost (float), net_profit (float), profit_margin_pct (float, 0 - 100 range), roi_ratio (float, ratio). Include this in the MCP tool schema as a 'returns' or output type specification.
• Expand the tool description to 100 - 200 characters explaining the business context: 'Calculates ROI and profit margins for a shopping cart after applying bundling discounts. Accepts a list of items (price, cost, quantity) and computes gross revenue, net profit, and margin percentage. Use this to model deal profitability before committing discounts.'
• Define cart_items parameter schema with field-level types: type: 'array', items: { type: 'object', properties: { price: { type: 'number', description: 'Unit price (USD, must be >= 0)' }, cost: { type: 'number', description: 'Unit cost (USD, must be >= 0)' }, quantity: { type: 'integer', description: 'Quantity (must be >= 1)' } }, required: ['price', 'cost', 'quantity'] }.
• Add range constraints to discount_pct: description should state 'Discount percentage to apply (0 - 100, e.g., 15 for 15% off). Defaults to 0 (no discount).' Add minimum: 0, maximum: 100 to the schema.
• Add input validation with clear error messages: if discount_pct < 0 or > 100, return error 'Invalid discount_pct: must be 0 - 100, got {value}'. If cart_items is empty, return error 'Empty cart provided; include at least one item with price, cost, and quantity.' If any item has negative price or cost, return error with the offending item.