diff --git a/docs/product/insights/ai/mcp/getting-started.mdx b/docs/product/insights/ai/mcp/getting-started.mdx
index 25e07c80f37d2..3e2401c62f417 100644
--- a/docs/product/insights/ai/mcp/getting-started.mdx
+++ b/docs/product/insights/ai/mcp/getting-started.mdx
@@ -8,15 +8,16 @@ Sentry MCP Observability helps you track and debug Model Context Protocol (MCP)
To start sending MCP data to Sentry, make sure you've created a Sentry project for your MCP-enabled repository and follow the guide below:
-## Requirements
-
-
-
-
## Supported SDKs
### JavaScript - MCP Server
+
+
The Sentry JavaScript SDK supports MCP observability by wrapping the MCP Server from the [@modelcontextprotocol/sdk](https://www.npmjs.com/package/@modelcontextprotocol/sdk) package. This wrapper automatically captures spans for your MCP server workflows including tool executions, resource access, and client connections.
#### Quick Start with MCP Server
@@ -41,3 +42,40 @@ const server = Sentry.wrapMcpServerWithSentry(new McpServer({
...
```
+
+### Python - MCP Server
+
+
+
+The Sentry Python SDK supports MCP observability for [FastMCP](https://gofastmcp.com/getting-started/welcome). The integration automatically captures spans for your MCP server workflows including tool executions, resource access, and prompt handling.
+
+#### Quick Start with FastMCP
+
+```python
+import sentry_sdk
+from mcp.server.fastmcp import FastMCP
+
+# Sentry init needs to be above everything else
+sentry_sdk.init(
+ dsn="___PUBLIC_DSN___",
+ traces_sample_rate=1.0,
+ # Optional: Enable to capture tool call arguments and results in Sentry, which may include PII
+ send_default_pii=True,
+)
+
+# Create the MCP server
+mcp = FastMCP("Example MCP Server")
+
+# Define a tool
+@mcp.tool()
+async def calculate_sum(a: int, b: int) -> int:
+ """Add two numbers together."""
+ return a + b
+
+# Run the server
+mcp.run()
+```