Definition
MCP (Model Context Protocol) servers are software components that implement a standardized protocol for connecting AI models and agents to external tools, data sources, and services. They act as bridges between LLMs and the outside world, providing a consistent interface through which AI systems can read data, execute actions, and interact with APIs — including web scraping and data extraction services.
How MCP Works
The Model Context Protocol defines a standard way for AI agents to discover and use tools:
Tool Discovery
An MCP server advertises its capabilities — what tools it offers, what parameters they accept, and what they return. An AI agent connecting to the server can enumerate these tools and understand how to invoke them.
Tool Invocation
When an AI agent needs to perform an action (like scraping a web page), it sends a structured request to the MCP server. The server executes the action and returns the result in a standard format.
Context Provision
MCP servers can also provide context — relevant data that helps the AI make better decisions. A scraping MCP server might provide page metadata, extraction capabilities, or available schemas.
MCP in the AI Ecosystem
MCP is becoming a standard integration layer for AI applications. Rather than building custom integrations for every tool an AI agent might use, developers implement MCP servers once and any MCP-compatible agent can use them.
Common MCP Server Types
- Data retrieval — web scraping, database queries, API access
- Code execution — running scripts, executing queries
- File operations — reading and writing files
- External services — email, messaging, payment processing
MCP and Web Scraping
An MCP server for web scraping allows any AI agent to fetch, render, and extract data from web pages through standardized tool calls. This integration means AI workflows can incorporate live web data without custom scraping code.
ScrapeGraphAI and MCP
ScrapeGraphAI provides MCP server integration, allowing AI agents to use its scraping and extraction capabilities through the Model Context Protocol. This enables seamless incorporation of web data collection into broader AI agent workflows and applications.