Claude Web Scraper MCP

The Claude Web Scraper MCP bridges the gap between a local web‑scraping engine and Claude for Desktop. It exposes the eGet web scraper as an MCP server, allowing AI assistants to request site content through a simple, standardized protocol. By delegating scraping to a local API, developers can keep data collection fast, private, and under their own control while still benefiting from Claude’s natural‑language interface.

Problem Solved

Web scraping is a common requirement in AI workflows—whether gathering training data, monitoring competitors, or pulling news feeds. Traditional approaches involve manually running scripts, handling authentication, and managing rate limits. When integrating with Claude, developers often need a way to trigger scrapes from within the assistant without leaving the conversation. This MCP server solves that friction by providing a ready‑to‑use endpoint that Claude can call directly, turning natural language requests into concrete HTTP calls to the eGet scraper.

What It Does and Why It Matters

The server listens for MCP commands, forwards them to the eGet API (), and returns structured results back to Claude. This abstraction lets developers focus on higher‑level logic—such as summarizing scraped content or extracting specific data points—while the MCP server handles network communication, error handling, and response formatting. For developers building AI‑driven data pipelines, this means less boilerplate code, easier debugging, and a consistent interface across different scraping backends.

Key Features

• Local API Integration: Connects directly to a locally running eGet instance, eliminating external network dependencies and ensuring data privacy.
• MCP Compatibility: Exposes a standard MCP interface that Claude for Desktop can consume out of the box.
• Command‑based Scraping: Accepts high‑level instructions like “scrape and summarize” or “fetch site info,” translating them into appropriate API calls.
• Extensible: Built on the framework, making it straightforward to add new tools or modify existing behavior.
• Developer‑friendly: Requires only Python 3.7+, a running eGet scraper, and minimal configuration in Claude’s desktop settings.

Use Cases

• Content Aggregation: Pull articles from news sites, summarize them, and feed the results into a knowledge base.
• Competitive Intelligence: Scrape product pages or pricing information on competitor sites and analyze trends via Claude.
• Data Enrichment: Enhance existing datasets with up‑to‑date web content, such as company profiles or regulatory filings.
• Research Automation: Quickly gather academic papers or conference schedules, then let Claude extract key insights.

Integration with AI Workflows

Once the MCP server is registered in Claude’s configuration, any conversation can include directives that trigger web scraping. The assistant interprets the user’s intent, constructs an MCP request, and streams the response back to the user. This seamless interaction eliminates context switching between the AI and external tools, enabling more natural, conversational data retrieval.

Unique Advantages

The most distinctive benefit is the local-first approach. By running eGet on the same machine as Claude, latency is minimized and sensitive data never leaves the local network. Additionally, because eGet is open source and highly configurable, developers can tweak scraping rules (headers, concurrency limits, parsers) without modifying the MCP server itself. This separation of concerns gives teams flexibility while maintaining a clean, protocol‑centric interface for AI assistants.