Server on AI Knowledge Base

Overview

Mon, 01 Jan 0001 00:00:00 +0000

Prompts

Mon, 01 Jan 0001 00:00:00 +0000

Prompts are the least commonly used of the three MCP primitives, but they fill an important niche: reusable, parameterized templates that help users invoke common workflows. Think of them as saved recipes that combine a specific prompt structure with dynamic arguments. Unlike tools and resources, prompts are user-initiated – the user explicitly selects a prompt from a menu rather than the model discovering it automatically. This makes them ideal for standardizing repetitive interactions like “summarize this codebase” or “review this PR.”

Resources

Mon, 01 Jan 0001 00:00:00 +0000

Resources are how MCP servers expose data to the model without requiring the model to “call” anything – think of them as files or documents the application can pull into context. The key distinction from tools is that resources are application-controlled (the host decides when to read them), while tools are model-controlled (the model decides when to invoke them). Pay attention to the URI-based addressing scheme, which lets clients discover and subscribe to resource updates. If your use case is primarily about providing context rather than performing actions, resources are usually the better primitive.

Tools

Mon, 01 Jan 0001 00:00:00 +0000

Tools are the most commonly used MCP primitive – they let the model invoke server-side functions with structured inputs and receive results. Focus on the JSON Schema-based input validation, which is how the model knows what arguments a tool accepts. A critical detail is that tool calls are model-initiated but require human approval in most host implementations, so design your tool descriptions to be clear enough that users understand what they are approving. Keep tool names concise and descriptions precise, as the model relies heavily on them for deciding when and how to call each tool.