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goswamig

Fetch MCP Server

by goswamig

fetch_html

Retrieve website content in HTML format by specifying the URL and optional headers using this MCP server tool. Ideal for extracting web data for analysis or integration.

Instructions

Fetch a website and return the content as HTML

Input Schema

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

Implementation Reference

  • The core handler function for the 'fetch_html' tool. It fetches the HTML content from the provided URL using the shared _fetch method and returns it wrapped in the expected MCP response format.
    static async html(requestPayload: RequestPayload) {
      try {
        const response = await this._fetch(requestPayload);
        const html = await response.text();
        return { content: [{ type: "text", text: html }], isError: false };
      } catch (error) {
        return {
          content: [{ type: "text", text: (error as Error).message }],
          isError: true,
        };
      }
    }
  • src/index.ts:110-112 (registration)
    The dispatch logic in the CallToolRequest handler that routes 'fetch_html' calls to Fetcher.html.
    if (request.params.name === "fetch_html") {
      const fetchResult = await Fetcher.html(validatedArgs);
      return fetchResult;
  • The input schema definition for the 'fetch_html' tool, registered in the ListTools response.
    inputSchema: {
      type: "object",
      properties: {
        url: {
          type: "string",
          description: "URL of the website to fetch",
        },
        headers: {
          type: "object",
          description: "Optional headers to include in the request",
        },
      },
      required: ["url"],
    },
  • Zod schema used for validating the input arguments to all fetch tools, including 'fetch_html'.
    export const RequestPayloadSchema = z.object({
      url: z.string().url(),
      headers: z.record(z.string()).optional(),
    });
  • Shared helper method for performing the HTTP fetch with custom User-Agent and error handling, used by the 'fetch_html' handler.
    export class Fetcher {
      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`);
          }
        }
      }
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 mentions fetching and returning HTML but doesn't cover important aspects like error handling, timeout behavior, authentication needs, rate limits, or whether it follows redirects. The description is minimal and lacks operational context.

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 extremely concise - a single sentence that directly states the tool's function. Every word earns its place with no redundancy or unnecessary elaboration. It's front-loaded with the core purpose.

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?

For a tool that performs network operations with no annotations and no output schema, the description is insufficient. It doesn't explain what happens with failed requests, what HTML is returned (full page vs. processed), or any behavioral characteristics. The minimal description leaves too many operational questions unanswered.

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%, so the schema already documents both parameters (url and headers) adequately. The description doesn't add any parameter-specific information beyond what's in the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 website'), specifying the return format ('as HTML'). It distinguishes from sibling tools like fetch_json and fetch_markdown by explicitly mentioning HTML output. However, it doesn't fully differentiate from fetch_txt which might also fetch websites but return plain text.

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 alternatives like fetch_json or fetch_markdown. It doesn't mention scenarios where HTML is preferred over other formats, nor does it discuss prerequisites or limitations. Usage context is implied but not explicitly stated.

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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