The Model Context Protocol (MCP) is an open standard developed by Anthropic that standardizes how AI models connect to external data sources and tools. Often compared to “USB-C for AI,” MCP provides a universal interface that allows AI applications to access real-time data from services like databases, APIs, file systems, and business tools without requiring custom integrations for each connection. The AI tools listed below support MCP, meaning they can connect to MCP-compatible servers and clients to enable more dynamic, context-aware workflows. Use this page to find AI tools that work with the MCP ecosystem.
FAQ
MCP (Model Context Protocol) is an open standard that lets AI models connect to external data and tools through a unified interface. Before MCP, each AI integration required custom API code. MCP standardizes this, making it easier to connect AI applications to your existing tools and data sources.
MCP has been adopted by a growing number of platforms and developer tools. Early adopters include Claude (Anthropic), Cursor, Replit, Zed, and Sourcegraph. Microsoft and AWS have also added MCP support to their AI services.
MCP is model-agnostic by design. While Anthropic developed it, the protocol works with any AI model that implements an MCP client. You can switch between different AI providers without rebuilding your integrations.
MCP is related but broader. Function calling is a feature within specific AI APIs. MCP provides a standardized protocol layer that works across multiple AI models and services, offering a consistent way to handle tools, resources, and prompts regardless of the underlying model.
