Minor docs updates

README.md

@@ -11,7 +11,7 @@
 
 </div>
 
-[Model Context Protocol (MCP)](https://modelcontextprotocol.io) servers are a standardized way to provide context and tools to your LLMs, and FastMCP makes building *and interacting with* them simple and intuitive. Create tools, expose resources, define prompts, and connect components with clean, Pythonic code.
+The [Model Context Protocol (MCP)](https://modelcontextprotocol.io) is a new, standardized way to provide context and tools to your LLMs, and FastMCP makes building MCP servers and clients simple and intuitive. Create tools, expose resources, define prompts, and connect components with clean, Pythonic code.
 
 ```python
 # server.py

docs/getting-started/welcome.mdx

@@ -7,7 +7,7 @@ icon: hand-wave
 ---
 
 
-[Model Context Protocol](https://modelcontextprotocol.io/) (MCP) servers are a new, standardized way to provide context and tools to your LLMs, and FastMCP makes building MCP servers simple and intuitive. Create tools, expose resources, define prompts, and more with clean, Pythonic code:
+The [Model Context Protocol](https://modelcontextprotocol.io/) (MCP) is a new, standardized way to provide context and tools to your LLMs, and FastMCP makes building MCP servers and clients simple and intuitive. Create tools, expose resources, define prompts, and more with clean, Pythonic code:
 
 ```python {1, 3, 5, 11}
 from fastmcp import FastMCP
@@ -25,7 +25,7 @@ if __name__ == "__main__":
 
 
 ## What is MCP?
-The Model Context Protocol (MCP) lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. It is often described as "the USB-C port for AI", providing a uniform way to connect LLMs to resources they can use. It may be easier to think of it as an API, but specifically designed for LLM interactions. MCP servers can:
+The Model Context Protocol lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. It is often described as "the USB-C port for AI", providing a uniform way to connect LLMs to resources they can use. It may be easier to think of it as an API, but specifically designed for LLM interactions. MCP servers can:
 
 - Expose data through **Resources** (think of these sort of like GET endpoints; they are used to load information into the LLM's context)
 - Provide functionality through **Tools** (sort of like POST endpoints; they are used to execute code or otherwise produce a side effect)