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Fetch MCP Server

by goswamig

fetch_json

Retrieve JSON data from a URL using the Fetch MCP Server. Specify the URL and optional headers to fetch and process JSON content for integration or analysis.

Instructions

Fetch a JSON file from a URL

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
headersNoOptional headers to include in the request
urlYesURL of the JSON to fetch

Implementation Reference

  • The static method `json()` that implements the core logic of the `fetch_json` tool: fetches the response using `_fetch`, parses JSON, stringifies it, and returns as text content or error.
    static async json(requestPayload: RequestPayload) {
      try {
        const response = await this._fetch(requestPayload);
        const json = await response.json();
        return {
          content: [{ type: "text", text: JSON.stringify(json) }],
          isError: false,
        };
      } catch (error) {
        return {
          content: [{ type: "text", text: (error as Error).message }],
          isError: true,
        };
      }
  • Zod schema `RequestPayloadSchema` used to validate input arguments (URL and optional headers) for `fetch_json` and other fetch tools.
    export const RequestPayloadSchema = z.object({
      url: z.string().url(),
      headers: z.record(z.string()).optional(),
    });
  • src/index.ts:83-100 (registration)
    Registration of the `fetch_json` tool in the `ListToolsRequestSchema` handler, defining name, description, and input schema.
    {
      name: "fetch_json",
      description: "Fetch a JSON file from a URL",
      inputSchema: {
        type: "object",
        properties: {
          url: {
            type: "string",
            description: "URL of the JSON to fetch",
          },
          headers: {
            type: "object",
            description: "Optional headers to include in the request",
          },
        },
        required: ["url"],
      },
    },
  • Private helper `_fetch` method used by `json()` (and other tools) to perform the HTTP request with custom User-Agent and error handling.
    private static async _fetch({
      url,
      headers,
    }: RequestPayload): Promise<Response> {
      try {
        const response = await fetch(url, {
          headers: {
            "User-Agent":
              "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
            ...headers,
          },
        });
    
        if (!response.ok) {
          throw new Error(`HTTP error: ${response.status}`);
        }
        return response;
      } catch (e: unknown) {
        if (e instanceof Error) {
          throw new Error(`Failed to fetch ${url}: ${e.message}`);
        } else {
          throw new Error(`Failed to fetch ${url}: Unknown error`);
        }
      }
  • Dispatch logic in the main `CallToolRequestSchema` handler that routes `fetch_json` calls to `Fetcher.json()`.
    if (request.params.name === "fetch_json") {
      const fetchResult = await Fetcher.json(validatedArgs);
      return fetchResult;
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions fetching from a URL but lacks details on error handling, timeouts, authentication needs, rate limits, or response format. For a network operation tool, this leaves critical behavioral traits unspecified, making it inadequate for safe and effective use.

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 a single, efficient sentence that directly states the tool's purpose without any fluff. It is front-loaded and appropriately sized for a simple tool, making it easy to parse and understand quickly. Every word earns its place, contributing to clarity.

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 of a network fetch operation, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., parsed JSON object, raw response), error conditions, or behavioral nuances. This lack of context makes it insufficient for an agent to use the tool reliably without additional assumptions.

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?

Schema description coverage is 100%, with clear descriptions for both parameters (url and headers). The description adds no additional parameter semantics beyond what the schema provides, such as examples or constraints. However, the baseline score of 3 is appropriate since the schema adequately documents the parameters, and no extra value is needed here.

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 action ('Fetch') and resource ('a JSON file from a URL'), making the purpose immediately understandable. It distinguishes from siblings by specifying JSON format (vs. HTML, markdown, or txt), though it doesn't explicitly contrast with them. The description is specific but could be more precise about the verb (e.g., 'Retrieve' or 'Download').

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?

No guidance is provided on when to use this tool versus the sibling tools (fetch_html, fetch_markdown, fetch_txt). The description implies usage for JSON files specifically, but it doesn't state alternatives, prerequisites, or exclusions. The agent must infer usage based on format alone, which is insufficient for clear decision-making.

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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