MCP Server Requests

Overview

The MCP Server Requests module supplies a lightweight HTTP client to AI assistants that speak the Model Context Protocol. By exposing a suite of REST‑like endpoints—GET, POST, PUT, DELETE, PATCH, and a specialized command—the server lets language models retrieve, manipulate, and analyze web content without leaving the MCP ecosystem. This capability is essential for assistants that need real‑time data, web scraping, or interaction with external APIs directly from a conversation.

Developers benefit because the server abstracts away the intricacies of HTTP request handling. The model can simply invoke a tool name (e.g., or ) and supply the URL, headers, or payload. The MCP server then performs the network call, applies optional content filtering, and returns a clean response that is easy for the model to ingest. The inclusion of full header visibility means models can inspect status codes, cookies, or custom response headers—useful for debugging or conditional logic in downstream tasks.

Key features include:

• Content conversion: HTML can be stripped of scripts and styles, optionally converted to Markdown for readability.
• Header flexibility: Custom or random User‑Agent strings, plus arbitrary request headers, enable mimicry of different browsers or authenticated sessions.
• HTTP method support: All common verbs are available, allowing the model to interact with REST APIs or perform CRUD operations on remote resources.
• Response introspection: Models receive the entire response object, not just the body, enabling them to react to status codes or headers.

Typical use cases span web‑scraping for up‑to‑date news, pulling data from public APIs (weather, finance, or social media), and automating form submissions. In a data‑driven workflow, an assistant can fetch a CSV file, convert it to Markdown, and feed the content back into a downstream model for analysis—all within a single conversation turn. The server’s design keeps the client side simple while providing robust, customizable HTTP capabilities that enhance the intelligence and autonomy of MCP‑enabled assistants.