Skip to main content
Glama
kwp-lab

MCP Fetch With Proxy

fetch

Retrieve web content as markdown with image URLs, using proxy support for accessing URLs and extracting text from internet sources.

Instructions

Retrieves URLs from the Internet and extracts their content as markdown. If images are found, their URLs will be included in the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
maxLengthNo
startIndexNo
rawNo

Implementation Reference

  • The primary handler for tool calls, which dispatches to the 'fetch' tool implementation. It validates input, fetches the URL, processes the content (markdown extraction, truncation), adds image list if present, and formats the response.
    server.setRequestHandler( CallToolSchema, async ( request: { method: "tools/call" params: { name: string; arguments?: Record<string, unknown> } }, extra: RequestHandlerExtra, ) => { try { const { name, arguments: args } = request.params if (name !== "fetch") { throw new Error(`Unknown tool: ${name}`) } const parsed = FetchArgsSchema.safeParse(args) if (!parsed.success) { throw new Error(`Invalid arguments: ${parsed.error}`) } const { content, prefix, imageUrls } = await fetchUrl( parsed.data.url, DEFAULT_USER_AGENT_AUTONOMOUS, parsed.data.raw, ) let finalContent = content if (finalContent.length > parsed.data.maxLength) { finalContent = finalContent.slice( parsed.data.startIndex, parsed.data.startIndex + parsed.data.maxLength, ) finalContent += `\n\n<e>Content truncated. Call the fetch tool with a start_index of ${ parsed.data.startIndex + parsed.data.maxLength } to get more content.</e>` } let imagesSection = "" if (imageUrls && imageUrls.length > 0) { imagesSection = "\n\nImages found in article:\n" + imageUrls.map((url) => `- ${url}`).join("\n") } return { content: [ { type: "text", text: `${prefix}Contents of ${parsed.data.url}:\n${finalContent}${imagesSection}`, }, ], } } catch (error) { return { content: [ { type: "text", text: `Error: ${error instanceof Error ? error.message : String(error)}`, }, ], isError: true, } } }, )
  • Input schema for the 'fetch' tool using Zod, defining parameters: url (required), maxLength, startIndex, raw.
    const FetchArgsSchema = z.object({ url: z.string().url(), maxLength: z.number().positive().max(1000000).default(20000), startIndex: z.number().min(0).default(0), raw: z.boolean().default(false), })
  • index.ts:168-181 (registration)
    Registration of the 'fetch' tool via the tools/list request handler, providing name, description, and input schema.
    server.setRequestHandler( ListToolsSchema, async (request: { method: "tools/list" }, extra: RequestHandlerExtra) => { const tools = [ { name: "fetch", description: "Retrieves URLs from the Internet and extracts their content as markdown. If images are found, their URLs will be included in the response.", inputSchema: zodToJsonSchema(FetchArgsSchema), }, ] return { tools } }, )
  • Core helper function that performs the HTTP fetch, determines if content is HTML, extracts readable markdown using Readability and Turndown if HTML, collects image URLs, or returns raw text with prefix.
    async function fetchUrl( url: string, userAgent: string, forceRaw = false, ): Promise<FetchResult> { const response = await fetch(url, { headers: { "User-Agent": userAgent }, }) if (!response.ok) { throw new Error(`Failed to fetch ${url} - status code ${response.status}`) } const contentType = response.headers.get("content-type") || "" const text = await response.text() const isHtml = text.toLowerCase().includes("<html") || contentType.includes("text/html") if (isHtml && !forceRaw) { const result = extractContentFromHtml(text, url) if (typeof result === "string") { return { content: result, prefix: "", } } const { markdown, images } = result const imageUrls = images.map((img) => img.src) return { content: markdown, prefix: "", imageUrls, } } return { content: text, prefix: `Content type ${contentType} cannot be simplified to markdown, but here is the raw content:\n`, } }
Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kwp-lab/mcp-fetch'

If you have feedback or need assistance with the MCP directory API, please join our Discord server