This MCP server provides tools for extracting web page content in various formats, including raw text, rendered HTML, and Markdown. It supports JavaScript-rendered pages and media files, enabling comprehensive web content retrieval and transformation. With environment configurations for AI media analysis, it is suitable for modern web scraping, data extraction, and content processing workflows.
Added on:
Created by:
Apr 04 2025
This MCP server provides tools for extracting web page content in various formats, including raw text, rendered HTML, and Markdown. It supports JavaScript-rendered pages and media files, enabling comprehensive web content retrieval and transformation. With environment configurations for AI media analysis, it is suitable for modern web scraping, data extraction, and content processing workflows.
Added on:
Created by:
Apr 04 2025
Tatsu
Featured
What is mcp-server-fetch-python?
The mcp-server-fetch-python is a versatile MCP server designed for fetching, transforming, and extracting web content. It offers multiple specialized tools: get-raw-text for direct text extraction, get-rendered-html for JavaScript-rendered pages, get-markdown for converting webpage content into Markdown format, and get-markdown-from-media for AI-powered content analysis of media files. It supports modern web applications, provides environment variables for AI integrations, and can be installed locally or used via server. This setup is ideal for developers needing efficient web scraping, data transformation, and content analysis automation.
Who will use mcp-server-fetch-python?
- Web developers
- Data analysts
- Content creators
- Web scraping professionals
- AI developers
How to use the mcp-server-fetch-python?
- Step1: Install or deploy the MCP server locally or configure via Claude Desktop
- Step2: Set environment variables like OPENAI_API_KEY if using media analysis
- Step3: Send URLs to the server using the supported tools for desired content extraction
- Step4: Retrieve and process the formatted content or raw data from the server
mcp-server-fetch-python's Core Features & Benefits
The Core Features
- get-raw-text
- get-rendered-html
- get-markdown
- get-markdown-from-media
The Benefits
- Supports JavaScript-rendered content
- Enables AI-powered media analysis
- Provides multiple output formats
- Supports local deployment and cloud integration
mcp-server-fetch-python's Main Use Cases & Applications
- Automated web data scraping and transformation
- Content extraction for research and data analysis
- Media content analysis with AI integration
- Web application content rendering and conversion
FAQs of mcp-server-fetch-python
Developer
- tatn
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Research And Data
A server implementation supporting Model Context Protocol, integrating CRIC's industrial AI capabilities.
Provides real-time traffic, air quality, weather, and bike-sharing data for Valencia city in a unified platform.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
A MCP client integrating Brave Search API for web searches, utilizing MCP protocol for efficient communication.
A protocol server enabling seamless communication between Umbraco CMS and external applications.
NOL integrates LangChain and Open Router to create a multi-client MCP server using Next.js
Connects LLMs to Firebolt Data Warehouse for autonomous querying, data access, and insight generation.
A client framework for connecting AI agents to MCP servers, enabling tool discovery and integration.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
An open-source client to interact with multiple MCP servers, enabling seamless tool access for Claude.
AI Chatbot
Integrates APIs, AI, and automation to enhance server and client functionalities dynamically.
Provides long-term memory for LLMs by storing and retrieving contextual information via MCP standards.
An advanced clinical evidence analysis server supporting precision medicine and oncology research with flexible search options.
A platform collecting A2A agents, tools, servers, and clients for effective agent communication and collaboration.
A Spring-based chatbot for Cloud Foundry that integrates with AI services, MCP, and memGPT for advanced capabilities.
An AI agent controlling macOS using OS-level tools, compatible with MCP, facilitating system management via AI.
PHP client library enabling interaction with MCP servers via SSE, StdIO, or external processes.
A platform for managing and deploying autonomous agents, tools, servers, and clients for automation tasks.
Enables interaction with powerful Text to Speech and video generation APIs for multimedia content creation.
An MCP server providing API access to RedNote (XiaoHongShu, xhs) for seamless integration.