What is MCP (Model Context Protocol)?
Model Context Protocol (MCP) is an open standard designed by Anthropic to bridge the gap between AI assistants and external data sources and make AI applications more relevant and context-aware.
Traditionally, AI models have struggled with integrating external data efficiently. The result has been fragmented implementations for each new data source.
MCP addresses this problem by providing a standardized framework for secure and scalable connections between AI tools and various systems.
How MCP works
MCP functions as a universal interface that allows AI tools to interact with content repositories, business platforms, and development environments. It supports secure two-way connections through MCP servers and clients:
- MCP servers expose data from external sources such as Google Drive, Slack, GitHub, Postgres, and Puppeteer.
- MCP clients (AI applications) connect to these servers to access structured information and enhance responses with relevant context.
Anthropic, the creator of MCP, has also provided SDKs, a local MCP server in the Claude Desktop app, and an open-source repository of MCP servers to facilitate easy adoption.
The number of MCP servers is growing fast. Companies like Block and Apollo have already integrated MCP, and developer tools such as Replit, Windsurf, and Cursor are using it to provide more effective coding assistance.
Example of an MCP server
Apify has built an MCP server that allows AI agents or frameworks that implement the MCP protocol to access all Apify Actors as tools for data extraction, web searching, and other tasks.
This implementation lets agents collect data from websites (e.g. Facebook posts, Google search results pages, URLs), summarize web trends, and execute automated workflows without requiring user intervention.
The Actors MCP Server supports multiple modes of interaction, including HTTP-based Server-Sent Events (SSE) and local stdin/stdout connections. Users can interact with the server through clients like Claude Desktop, LibreChat, and Apify’s Tester MCP Client.
Why Model Context Protocol matters
MCP marks a shift from isolated AI models to connected, real-world applications. Instead of maintaining separate integrations for each tool, developers can rely on a single protocol. This simplifies AI deployments across different environments. As MCP adoption grows, AI assistants will become more adept at retrieving and using external data for more informed and accurate responses.
