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psaboia
by psaboia

httpbin_json

Test and validate JSON responses from HTTP requests in the MCP Server Playground for development and debugging purposes.

Instructions

Returns data about slide show

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aNo

Implementation Reference

  • Handler implementation for the 'httpbin_json' tool. Fetches JSON data from 'https://httpbin.org/json' using GET request and returns the parsed data as toolResult.
    if (request.params.name === "httpbin_json") {
        try {
          const response = await fetch('https://httpbin.org/json', {
            method: 'GET',
            headers: {
              'accept': 'application/json'
            }
          });
          
          if (!response.ok) {
            throw new Error(`HTTP error! status: ${response.status}`);
          }
          
          const data = await response.json();
          return { toolResult: data };
    
        } catch (error) {
          throw new Error("Something went wrong");
    
        }
      
      
    }
  • src/index.ts:36-46 (registration)
    Tool registration in the ListTools response, defining name, description, and input schema for 'httpbin_json'.
    {
      name: "httpbin_json",
      description: "Returns data about slide show ",
      inputSchema: {
        type: "object",
        properties: {
          a: { type: "number" },
        },
        required: []
      }
    }
  • Input schema definition for the 'httpbin_json' tool, specifying an optional 'a' property of type number.
    inputSchema: {
      type: "object",
      properties: {
        a: { type: "number" },
      },
      required: []
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Returns data', which suggests a read-only operation, but doesn't specify any behavioral traits like error handling, rate limits, authentication needs, or what 'slide show' refers to. This leaves significant gaps in understanding how the tool behaves.

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

Conciseness3/5

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

The description is a single sentence that is concise, but it's under-specified rather than efficiently informative. It's front-loaded but lacks substance, making it borderline adequate in structure but not truly helpful.

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 complexity (1 parameter, no annotations, no output schema), the description is incomplete. It doesn't explain what data is returned, how 'a' is used, or any context about slide shows, leaving the agent with insufficient information to effectively use the tool.

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

Parameters2/5

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

The input schema has 1 parameter 'a' of type number with 0% description coverage, and the description adds no information about parameters. It doesn't explain what 'a' represents, how it relates to slide shows, or its purpose, failing to compensate for the low schema coverage.

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

Purpose2/5

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

The description states the tool 'Returns data about slide show', which provides a vague purpose without specifying what kind of data or what operation is performed. It doesn't clearly distinguish from the sibling tool 'calculate_sum', and while it's not a tautology (it adds 'about slide show'), it remains too general to be helpful for precise tool selection.

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?

There is no guidance on when to use this tool versus the sibling 'calculate_sum' or any alternatives. The description implies it's for slide show data, but without context on when it's appropriate or what scenarios it addresses, leaving the agent with minimal usage direction.

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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