Extract protocol types into a standalone mcp-types package

Convert the repository into a uv workspace mirroring pydantic/httpx2. The
root pyproject becomes a pure coordinator (package = false) and the two
distributable packages live nested under src/<pkg>/<pkg>/ each with their
own pyproject:

- src/mcp/mcp/ -> mcp
- src/mcp-types/mcp_types/ -> mcp-types (import mcp_types)

The protocol types (_types.py, jsonrpc.py) move into mcp_types, which only
depends on pydantic and typing-extensions. mcp depends on mcp-types via
uv-dynamic-versioning, so installing mcp still pulls the types in. The
mcp.types module path is removed; all imports now use mcp_types. The
curated re-exports on the top-level mcp package are unchanged.

Author: Kludex

README.v2.md

@@ -412,10 +412,10 @@ For full control over tool responses including the `_meta` field (for passing da
 
 from typing import Annotated
 
+from mcp_types import CallToolResult, TextContent
 from pydantic import BaseModel
 
 from mcp.server.mcpserver import MCPServer
-from mcp.types import CallToolResult, TextContent
 
 mcp = MCPServer("CallToolResult Example")
 
@@ -732,9 +732,10 @@ uv run completion-client
 import asyncio
 import os
 
+from mcp_types import PromptReference, ResourceTemplateReference
+
 from mcp import ClientSession, StdioServerParameters
 from mcp.client.stdio import stdio_client
-from mcp.types import PromptReference, ResourceTemplateReference
 
 # Create server parameters for stdio connection
 server_params = StdioServerParameters(
@@ -821,11 +822,11 @@ like OAuth flows, credential collection, or payment processing.
 
 import uuid
 
+from mcp_types import ElicitRequestURLParams
 from pydantic import BaseModel, Field
 
 from mcp.server.mcpserver import Context, MCPServer
 from mcp.shared.exceptions import UrlElicitationRequiredError
-from mcp.types import ElicitRequestURLParams
 
 mcp = MCPServer(name="Elicitation Example")
 
@@ -929,8 +930,9 @@ Tools can interact with LLMs through sampling (generating text):
 
 <!-- snippet-source examples/snippets/servers/sampling.py -->
 ```python
+from mcp_types import SamplingMessage, TextContent
+
 from mcp.server.mcpserver import Context, MCPServer
-from mcp.types import SamplingMessage, TextContent
 
 mcp = MCPServer(name="Sampling Example")
 
@@ -1639,8 +1641,9 @@ from collections.abc import AsyncIterator
 from contextlib import asynccontextmanager
 from typing import TypedDict
 
+import mcp_types as types
+
 import mcp.server.stdio
-from mcp import types
 from mcp.server import Server, ServerRequestContext
 
 
@@ -1751,8 +1754,9 @@ uv run examples/snippets/servers/lowlevel/basic.py
 
 import asyncio
 
+import mcp_types as types
+
 import mcp.server.stdio
-from mcp import types
 from mcp.server import Server, ServerRequestContext
 
 
@@ -1828,8 +1832,9 @@ uv run examples/snippets/servers/lowlevel/structured_output.py
 import asyncio
 import json
 
+import mcp_types as types
+
 import mcp.server.stdio
-from mcp import types
 from mcp.server import Server, ServerRequestContext
 
 
@@ -1920,8 +1925,9 @@ uv run examples/snippets/servers/lowlevel/direct_call_tool_result.py
 
 import asyncio
 
+import mcp_types as types
+
 import mcp.server.stdio
-from mcp import types
 from mcp.server import Server, ServerRequestContext
 
 
@@ -1991,7 +1997,8 @@ For servers that need to handle large datasets, the low-level server provides pa
 ```python
 """Example of implementing pagination with the low-level MCP server."""
 
-from mcp import types
+import mcp_types as types
+
 from mcp.server import Server, ServerRequestContext
 
 # Sample data to paginate
@@ -2037,9 +2044,10 @@ _Full example: [examples/snippets/servers/pagination_example.py](https://github.
 
 import asyncio
 
+from mcp_types import PaginatedRequestParams, Resource
+
 from mcp.client.session import ClientSession
 from mcp.client.stdio import StdioServerParameters, stdio_client
-from mcp.types import PaginatedRequestParams, Resource
 
 
 async def list_all_resources() -> None:
@@ -2099,7 +2107,9 @@ uv run client
 import asyncio
 import os
 
-from mcp import ClientSession, StdioServerParameters, types
+import mcp_types as types
+
+from mcp import ClientSession, StdioServerParameters
 from mcp.client.context import ClientRequestContext
 from mcp.client.stdio import stdio_client
 

docs/experimental/tasks-client.md

@@ -12,7 +12,7 @@ Call a tool as a task and poll for the result:
 
 ```python
 from mcp.client.session import ClientSession
-from mcp.types import CallToolResult
+from mcp_types import CallToolResult
 
 async with ClientSession(read, write) as session:
     await session.initialize()
@@ -96,7 +96,7 @@ The elicitation callback (set during session creation) handles the actual user i
 To handle elicitation requests from the server, provide a callback when creating the session:
 
 ```python
-from mcp.types import ElicitRequestParams, ElicitResult
+from mcp_types import ElicitRequestParams, ElicitResult
 
 async def handle_elicitation(context, params: ElicitRequestParams) -> ElicitResult:
     # Display the message to the user
@@ -125,7 +125,7 @@ async with ClientSession(
 Similarly, handle sampling requests with a callback:
 
 ```python
-from mcp.types import CreateMessageRequestParams, CreateMessageResult, TextContent
+from mcp_types import CreateMessageRequestParams, CreateMessageResult, TextContent
 
 async def handle_sampling(context, params: CreateMessageRequestParams) -> CreateMessageResult:
     # In a real implementation, call your LLM here
@@ -207,7 +207,7 @@ Register task handlers to declare what task-augmented requests your client accep
 
 ```python
 from mcp.client.experimental.task_handlers import ExperimentalTaskHandlers
-from mcp.types import (
+from mcp_types import (
     CreateTaskResult, GetTaskResult, GetTaskPayloadResult,
     TaskMetadata, ElicitRequestParams,
 )
@@ -283,7 +283,7 @@ A client that handles all task scenarios:
 import anyio
 from mcp.client.session import ClientSession
 from mcp.client.stdio import stdio_client
-from mcp.types import CallToolResult, ElicitRequestParams, ElicitResult
+from mcp_types import CallToolResult, ElicitRequestParams, ElicitResult
 
 
 async def elicitation_callback(context, params: ElicitRequestParams) -> ElicitResult:

docs/experimental/tasks-server.md

@@ -13,7 +13,7 @@ The simplest way to add task support:
 ```python
 from mcp.server import Server
 from mcp.server.experimental.task_context import ServerTaskContext
-from mcp.types import CallToolResult, CreateTaskResult, TextContent, Tool, ToolExecution, TASK_REQUIRED
+from mcp_types import CallToolResult, CreateTaskResult, TextContent, Tool, ToolExecution, TASK_REQUIRED
 
 server = Server("my-server")
 server.experimental.enable_tasks()  # Registers all task handlers automatically
@@ -58,7 +58,7 @@ That's it. `enable_tasks()` automatically:
 Tools declare task support via the `execution.taskSupport` field:
 
 ```python
-from mcp.types import Tool, ToolExecution, TASK_REQUIRED, TASK_OPTIONAL, TASK_FORBIDDEN
+from mcp_types import Tool, ToolExecution, TASK_REQUIRED, TASK_OPTIONAL, TASK_FORBIDDEN
 
 Tool(
     name="my_tool",
@@ -199,7 +199,7 @@ async def work(task: ServerTaskContext) -> CallToolResult:
 Tasks can request LLM completions from the client:
 
 ```python
-from mcp.types import SamplingMessage, TextContent
+from mcp_types import SamplingMessage, TextContent
 
 async def work(task: ServerTaskContext) -> CallToolResult:
     await task.update_status("Generating response...")
@@ -256,7 +256,7 @@ For production, implement `TaskStore` with persistent storage:
 
 ```python
 from mcp.shared.experimental.tasks.store import TaskStore
-from mcp.types import Task, TaskMetadata, Result
+from mcp_types import Task, TaskMetadata, Result
 
 class RedisTaskStore(TaskStore):
     def __init__(self, redis_client):
@@ -299,7 +299,7 @@ A server with multiple task-supporting tools:
 ```python
 from mcp.server import Server
 from mcp.server.experimental.task_context import ServerTaskContext
-from mcp.types import (
+from mcp_types import (
     CallToolResult, CreateTaskResult, TextContent, Tool, ToolExecution,
     SamplingMessage, TASK_REQUIRED,
 )
@@ -412,7 +412,7 @@ import uvicorn
 
 from mcp.server import Server
 from mcp.server.experimental.task_context import ServerTaskContext
-from mcp.types import (
+from mcp_types import (
     CallToolResult, CreateTaskResult, TextContent, Tool, ToolExecution, TASK_REQUIRED,
 )
 
@@ -468,7 +468,7 @@ Test task functionality with the SDK's testing utilities:
 import pytest
 import anyio
 from mcp.client.session import ClientSession
-from mcp.types import CallToolResult
+from mcp_types import CallToolResult
 
 
 @pytest.mark.anyio

docs/experimental/tasks.md

@@ -102,7 +102,7 @@ Server                              Client
 When augmenting a request with task execution, include `TaskMetadata`:
 
 ```python
-from mcp.types import TaskMetadata
+from mcp_types import TaskMetadata
 
 task = TaskMetadata(ttl=60000)  # TTL in milliseconds
 ```
@@ -143,7 +143,7 @@ The SDK manages these automatically when you enable task support.
 ```python
 from mcp.server import Server
 from mcp.server.experimental.task_context import ServerTaskContext
-from mcp.types import CallToolResult, TextContent, TASK_REQUIRED
+from mcp_types import CallToolResult, TextContent, TASK_REQUIRED
 
 server = Server("my-server")
 server.experimental.enable_tasks()  # One-line setup
@@ -165,7 +165,7 @@ async def handle_tool(name: str, arguments: dict):
 
 ```python
 from mcp.client.session import ClientSession
-from mcp.types import CallToolResult
+from mcp_types import CallToolResult
 
 async with ClientSession(read, write) as session:
     await session.initialize()