Design and Implementation of MCP-Web-Curl: A Model Context Protocol Server for Web and API Access in Agentic Coding Assistants

Rayhan Zahwan Saleh; Muharman Lubis

doi:10.15408/jti.v19i1.49625

Authors

Rayhan Zahwan Saleh Information System Study Program, School of Industrial Engineering, Telkom University
Muharman Lubis Information System Study Program, School of Industrial Engineering, Telkom University

DOI:

https://doi.org/10.15408/jti.v19i1.49625

Keywords:

Model Context Protocol, MCP-Web-Curl, agentic AI, agentic coder, web scraping, REST API

Abstract

Many contemporary agentic coding assistants expose large language models through API wrappers but still lack a generic, reliable way to read the live web or invoke arbitrary REST endpoints, when relevant documentation or error explanations fall outside their internal context, these agents often stop rather than extend the search space. To address this gap, this paper presents MCP-Web-Curl, a Node.js/TypeScript based Model Context Protocol (MCP) server and command-line interface that provides LLM oriented tools for browser-based web scraping, REST API requests, Google Custom Search, smart routing over natural language commands, and robust file downloading. MCP-Web-Curl is designed around strict character limits, explicit truncation metadata, and resource blocking so that external calls remain token efficient and predictable for agent planning. Using a design science approach, we elicit requirements from real world agentic coder usage, design a modular architecture, implement the server with Puppeteer and the official MCP SDK, and evaluate it qualitatively through documentation-reading, API inspection, and download scenarios, complemented by independent marketplace reviews on MCPlane, Glama, and related MCP catalogs. The resulting architecture positions MCP-Web-Curl as a reusable blueprint for generic web/API access layers in agentic coding environments.

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