Upgrade Python libraries to mcp 2.2.0, and bump others as well

mcp-client-python/README.md

@@ -43,4 +43,4 @@ Without an `ANTHROPIC_API_KEY`, the client still connects, prints the server's t
 
 The two channels go to different readers: `content` is forwarded to the model, while `structured_content` is used as data — when a tool returns an array, the client counts its items rather than re-reading the prose. See [Structured Content](https://modelcontextprotocol.io/specification/2026-07-28/server/tools#structured-content).
 
-`Client(transport, mode="auto")` probes `server/discover` and falls back to the `2025-11-25` handshake; `client.protocol_version` reports which era you got. See [Protocol versions](https://py.sdk.modelcontextprotocol.io/v2/protocol-versions/).
+`Client(server_params, mode="auto")` launches the server from its `StdioServerParameters`, then probes `server/discover` and falls back to the `2025-11-25` handshake; `client.protocol_version` reports which era you got. See [Protocol versions](https://py.sdk.modelcontextprotocol.io/v2/protocol-versions/).

mcp-client-python/client.py

@@ -6,7 +6,6 @@
 from anthropic import Anthropic
 from dotenv import load_dotenv
 from mcp import Client, StdioServerParameters
-from mcp.client.stdio import stdio_client
 from mcp_types import TextContent
 
 load_dotenv()  # load environment variables from .env
@@ -54,10 +53,9 @@ async def connect_to_server(self, server_script_path: str):
         else:
             server_params = StdioServerParameters(command="node", args=[server_script_path], env=None)
 
+        # Client launches the command itself when given StdioServerParameters.
         # "auto" probes server/discover, falling back to the 2025-11-25 handshake.
-        self.client = await self.exit_stack.enter_async_context(
-            Client(stdio_client(server_params), mode="auto")
-        )
+        self.client = await self.exit_stack.enter_async_context(Client(server_params, mode="auto"))
 
         # List available tools
         response = await self.client.list_tools()
@@ -106,9 +104,7 @@ async def process_query(self, query: str) -> str:
                     {
                         "type": "tool_result",
                         "tool_use_id": tool_use.id,
-                        "content": "\n".join(
-                            block.text for block in result.content if isinstance(block, TextContent)
-                        ),
+                        "content": "\n".join(block.text for block in result.content if isinstance(block, TextContent)),
                         "is_error": bool(result.is_error),
                     }
                 )

mcp-client-python/pyproject.toml

@@ -5,11 +5,11 @@ description = "A simple MCP client"
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-    "anthropic>=0.87.0",
-    "mcp>=2.0.0",
+    "anthropic>=1.4.0",
+    "mcp>=2.2.0",
     # client.py imports TextContent from mcp_types, which `mcp` pins exactly.
-    "mcp-types>=2.0.0",
-    "python-dotenv>=1.2.2",
+    "mcp-types>=2.2.0",
+    "python-dotenv>=1.2.3",
 ]
 
 [dependency-groups]

weather-server-python/pyproject.toml

@@ -8,7 +8,7 @@ requires-python = ">=3.10"
 # install a second HTTP stack alongside it.
 dependencies = [
     "httpx2>=2.12.0",
-    "mcp[cli]>=2.0.0",
+    "mcp[cli]>=2.2.0",
     # weather.py imports BaseModel, Field, and RootModel directly. RootModel is v2-only.
     "pydantic>=2.0.0",
 ]

weather-server-python/weather.py

@@ -2,6 +2,7 @@
 
 import httpx2
 from mcp.server import MCPServer
+from mcp.server.mcpserver.exceptions import ToolError
 from pydantic import BaseModel, Field, RootModel
 
 # Initialize the MCP server
@@ -74,7 +75,7 @@ async def get_alerts(state: str) -> Alerts:
     data = await make_nws_request(url)
 
     if not data or "features" not in data:
-        raise ValueError(f"Unable to fetch alerts for {state.upper()}.")
+        raise ToolError(f"Unable to fetch alerts for {state.upper()}.")
 
     # An empty result is an empty array, not an error.
     #
@@ -107,18 +108,18 @@ async def get_forecast(latitude: float, longitude: float) -> Forecast:
     points_data = await make_nws_request(points_url)
 
     if not points_data:
-        raise ValueError("Unable to fetch forecast data for this location.")
+        raise ToolError("Unable to fetch forecast data for this location.")
 
     # Get the forecast URL from the points response
     forecast_url = points_data["properties"]["forecast"]
     forecast_data = await make_nws_request(forecast_url)
 
     if not forecast_data:
-        raise ValueError("Unable to fetch detailed forecast.")
+        raise ToolError("Unable to fetch detailed forecast.")
 
     periods = forecast_data["properties"]["periods"][:5]  # Only show next 5 periods
     if not periods:
-        raise ValueError("No forecast periods available.")
+        raise ToolError("No forecast periods available.")
 
     return Forecast(
         latitude=latitude,