Why this server?

Enables fetching web content using the Node.js undici library, supporting various HTTP methods, content formats, and request configurations.

Why this server?

A server that provides AgentQL's data extraction capabilities enabling AI agents to get structured data from unstructured web

Why this server?

A Server-Sent Events implementation using FastAPI framework that integrates Model Context Protocol (MCP), allowing AI models to access external tools and data sources like weather information.

Why this server?

Provides functionality to fetch web content in various formats, including HTML, JSON, plain text, and Markdown.

Why this server?

A server based on the MCP protocol that uses the Brave API for web search functionality.

Why this server?

🔍 A Model Context Protocol (MCP) server providing unified access to multiple search engines (Tavily, Brave, Kagi), AI tools (Perplexity, FastGPT), and content processing services (Jina AI, Kagi). Combines search, AI responses, content processing, and enhancement features through a single interface.

Why this server?

Provides web search functionality via DuckDuckGo for Claude Code and MCP-compatible clients, featuring advanced content exploration, navigation across search results, and detailed webpage analysis.

Why this server?

An MCP server that connects any MCP client (like Claude or Cursor) with the browser using browser-use, allowing clients to utilize existing LLMs without requiring additional API keys.

Why this server?

A simple MCP server that facilitates website fetching through a configurable server platform using stdio or SSE transport, allowing integration with tools like Cursor for streamlined access.

Why this server?

Enables retrieval and processing of web page content for LLMs by converting HTML to markdown, with support for content truncation and pagination.