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bahfahh

Basic Math MCP Server

sum

Add two numbers together to calculate their total. Input two numeric values to perform basic addition.

Instructions

Add two numbers together

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aYesFirst number
bYesSecond number

Implementation Reference

  • The handler function for the 'sum' tool that adds two numbers and returns a text response.
    async ({ a, b }: { a: number; b: number }) => {
      const result = a + b;
      return {
        content: [
          {
            type: "text",
            text: `The sum of ${a} and ${b} is: ${result}`
          }
        ]
      };
    }
  • Zod schema defining input parameters 'a' and 'b' as numbers for the 'sum' tool.
      a: z.number().describe("First number"),
      b: z.number().describe("Second number")
    },
  • src/index.ts:23-41 (registration)
    Registration of the 'sum' tool on the MCP server with name, description, input schema, and handler function.
    server.tool(
      "sum",
      "Add two numbers together",
      {
        a: z.number().describe("First number"),
        b: z.number().describe("Second number")
      },
      async ({ a, b }: { a: number; b: number }) => {
        const result = a + b;
        return {
          content: [
            {
              type: "text",
              text: `The sum of ${a} and ${b} is: ${result}`
            }
          ]
        };
      }
    );
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic function without mentioning any behavioral traits like error handling, performance characteristics, or what happens with non-numeric inputs. This leaves significant gaps for an AI agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise at just four words, front-loading the essential information with zero wasted words. Every word earns its place in communicating the core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what the tool returns (sum result format), error conditions, or behavioral constraints. For even a simple tool, this leaves the AI agent with incomplete operational understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage with clear parameter documentation, so the description doesn't need to add parameter details. The description doesn't provide any additional parameter semantics beyond what's in the schema, which is acceptable given the comprehensive schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Add') and resource ('two numbers'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from the sibling 'subtraction' tool, which would be helpful for an AI agent choosing between them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus the sibling 'subtraction' tool, nor any context about appropriate use cases. It simply states what the tool does without addressing when it should be selected.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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