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content/ai-system/advanced-apis/index.md

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 MCP's architecture is composed of three types of applications: hosts, servers, and clients. **Hosts** are AI applications that users interact with directly, such as Claude Code and IDEs. These applications contain LLMs that need access to external capabilities. **Servers** are external applications that expose specific capabilities to AI models through standardized interfaces. These might include database connectors, file system access tools, or API integrations with third-party services. **Clients** live within host applications and manage connections between hosts and servers. Each client maintains a dedicated one-to-one connection with a specific server, similar to how we saw individual connections in our previous protocol examples.
 
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 MCP servers can provide three types of capabilities to AI systems: resources, tools, and prompts. **Resources** act like read-only data sources, similar to HTTP `GET` endpoints. They provide contextual information without performing significant computation or causing side effects. For example, a file system resource might provide access to documentation, while a database resource could offer read-only access to customer data. **Tools** are executable functions that AI models can call to perform specific actions. Unlike resources, tools can modify state, perform computations, or interact with external services. Examples include sending emails, creating calendar events, or running data analysis scripts. **Prompts** are pre-defined templates that help AI systems use resources and tools most effectively. They provide structured ways to accomplish common tasks and can be shared across different AI applications.