diff --git a/README.md b/README.md
index c1384c638..91593ea73 100644
--- a/README.md
+++ b/README.md
@@ -33,6 +33,9 @@
 >
 > **For production MCP applications, install FastMCP:** `pip install fastmcp`
 
+> [!Important]
+> FastMCP 3.0 is in development and may include breaking changes. To avoid unexpected issues, pin your dependency to v2: `fastmcp<3`
+
 ---
 
 **FastMCP is the standard framework for building MCP applications**, providing the fastest path from idea to production.
diff --git a/docs/getting-started/installation.mdx b/docs/getting-started/installation.mdx
index edcaa5983..ff9bb929a 100644
--- a/docs/getting-started/installation.mdx
+++ b/docs/getting-started/installation.mdx
@@ -23,6 +23,10 @@ Alternatively, you can install it directly with `pip` or `uv pip`:
     ```
 </CodeGroup>
 
+<Warning>
+**FastMCP 3.0** is in development and may include breaking changes. To avoid unexpected issues, pin your dependency to v2: `fastmcp<3`
+</Warning>
+
 ### Verify Installation
 
 To verify that FastMCP is installed correctly, you can run the following command:
diff --git a/docs/getting-started/welcome.mdx b/docs/getting-started/welcome.mdx
index f424497ee..bbba67535 100644
--- a/docs/getting-started/welcome.mdx
+++ b/docs/getting-started/welcome.mdx
@@ -35,7 +35,6 @@ if __name__ == "__main__":
     mcp.run()
 ```
 
-
 ## Beyond Basic MCP
 
 FastMCP pioneered Python MCP development, and FastMCP 1.0 was incorporated into the [official MCP SDK](https://github.com/modelcontextprotocol/python-sdk) in 2024.
@@ -46,6 +45,10 @@ Ready to build? Start with our [installation guide](/getting-started/installatio
 
 FastMCP is made with 💙 by [Prefect](https://www.prefect.io/).
 
+<Warning>
+**FastMCP 3.0** is in development and may include breaking changes. To avoid unexpected issues, pin your dependency to v2: `fastmcp<3`
+</Warning>
+
 ## What is MCP?
 
 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: