The Model Context Protocol (MCP) is an open standard designed to simplify how AI assistants, like chatbots or virtual helpers, connect with various data sources and tools. Think of MCP as a universal adapter that allows AI systems to easily access and interact with different information repositories and applications without needing custom integrations for each one.
Key Components of MCP:
- MCP Hosts: These are AI applications or interfaces (like chatbots) that need to access external data or functionalities.
- MCP Clients: Acting as intermediaries, these manage secure connections between the AI application (host) and the external data sources or tools (servers)
- MCP Servers: These are programs that provide specific capabilities, such as access to databases, communication platforms, or other services. They connect to various data sources like Google Drive, Slack, GitHub, databases, and web browsers.
Benefits of MCP:
- Standardization: By providing a common protocol, MCP eliminates the need for custom connectors for each data source, making integrations more straightforward and scalable.
- Real-Time Interaction: MCP supports two-way, real-time communication, allowing AI assistants to both retrieve information and perform actions dynamically.
- Flexibility: With MCP, AI systems can dynamically discover and interact with available tools without hard-coded knowledge of each integration, enhancing adaptability.
Resources
https://docs.anthropic.com/en/docs/agents-and-tools/mcp
https://www.youtube.com/watch?v=eur8dUO9mvE
https://mcp.so/
https://github.com/docker/mcp-servers
https://github.com/modelcontextprotocol/servers/tree/main