webmcp-tool-schemas

WebMCP Tool Schema Design

Before writing code

Fetch live docs:

1. Fetch https://webmachinelearning.github.io/webmcp/ for the inputSchema specification and any constraints
2. Web-search webmcp inputSchema JSON Schema requirements for schema format details
3. Web-search JSON Schema draft specification for the JSON Schema version used by WebMCP
4. Web-search webmcp tool schema best practices for community guidance

Conceptual Architecture

Role of Schemas in WebMCP

The inputSchema in a tool definition serves two purposes:

1. Agent guidance — The agent reads the schema to understand what parameters to provide
2. Input validation — The browser validates agent-provided input against the schema before calling execute

Schema Structure

WebMCP uses standard JSON Schema. Each tool's inputSchema is a JSON Schema object:

inputSchema: {
  type: "object",
  properties: {
    paramName: { type: "string", description: "What this parameter is" },
    // ...more properties
  },
  required: ["paramName"]
}

Property Types

JSON Schema Type	Use For	Example
string	Text, IDs, codes	Product ID, search query, coupon code
number	Decimal values	Price, weight, rating
integer	Whole numbers	Quantity, page number
boolean	True/false flags	In-stock filter, gift wrap option
array	Lists	Product IDs, selected categories
object	Nested structures	Address, payment details

Description Annotations

Always add description to properties — agents use these to decide what values to provide:

properties: {
  query: {
    type: "string",
    description: "Search keywords for product catalog"
  },
  maxPrice: {
    type: "number",
    description: "Maximum price in USD. Omit to search all prices."
  }
}

Constraints

Use JSON Schema constraints to guide agent input:

• minLength / maxLength for strings
• minimum / maximum for numbers
• enum for fixed value sets
• pattern for regex validation
• minItems / maxItems for arrays
• default for optional parameters with defaults

Commerce Schema Patterns

Product search:

{
  type: "object",
  properties: {
    query: { type: "string", description: "Search keywords" },
    category: { type: "string", enum: ["electronics", "clothing", "home"] },
    maxPrice: { type: "number", minimum: 0 },
    sortBy: { type: "string", enum: ["relevance", "price_asc", "price_desc", "rating"] }
  },
  required: ["query"]
}

Add to cart:

{
  type: "object",
  properties: {
    productId: { type: "string", description: "Product identifier" },
    quantity: { type: "integer", minimum: 1, maximum: 99, default: 1 },
    variant: { type: "string", description: "Size, color, or variant ID" }
  },
  required: ["productId"]
}

Shipping address:

{
  type: "object",
  properties: {
    street: { type: "string" },
    city: { type: "string" },
    state: { type: "string" },
    zipCode: { type: "string", pattern: "^[0-9]{5}(-[0-9]{4})?$" },
    country: { type: "string", enum: ["US", "CA", "UK"] }
  },
  required: ["street", "city", "state", "zipCode", "country"]
}

Output Conventions

While WebMCP doesn't formally specify an output schema, tools should return predictable JSON:

• Always include a status or success field
• Return structured data, not HTML or plain text
• Include pagination info for list results (total, page, pageSize)
• Return error objects with code and message for failures

Schema Design Principles

1. Minimal surface — Only require parameters the tool actually needs
2. Descriptive — Every property should have a description
3. Constrained — Use enum, minimum, maximum to prevent invalid inputs
4. Flat when possible — Avoid deep nesting; agents handle flat schemas better
5. Consistent — Use the same naming conventions across all tools (camelCase)
6. No sensitive data — Never ask for passwords, SSNs, or full card numbers in schemas

Fetch the WebMCP spec for the exact JSON Schema version supported and any WebMCP-specific constraints before designing schemas.