refactor: replace lowlevel Server decorators with on_* constructor kwargs (#1985)

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Max Isbey 2026-02-12 15:55:54 +00:00 • committed by GitHub
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@ -351,7 +351,6 @@ The nested `RequestParams.Meta` Pydantic model class has been replaced with a to
- `RequestParams.Meta` (Pydantic model) → `RequestParamsMeta` (TypedDict)
- Attribute access (`meta.progress_token`) → Dictionary access (`meta.get("progress_token")`)
- `progress_token` field changed from `ProgressToken | None = None` to `NotRequired[ProgressToken]`
`
**In request context handlers:**
@ -364,11 +363,12 @@ async def handle_tool(name: str, arguments: dict) -> list[TextContent]:
await ctx.session.send_progress_notification(ctx.meta.progress_token, 0.5, 100)
# After (v2)
@server.call_tool()
async def handle_tool(name: str, arguments: dict) -> list[TextContent]:
ctx = server.request_context
async def handle_call_tool(ctx: ServerRequestContext, params: CallToolRequestParams) -> CallToolResult:
if ctx.meta and "progress_token" in ctx.meta:
await ctx.session.send_progress_notification(ctx.meta["progress_token"], 0.5, 100)
...
server = Server("my-server", on_call_tool=handle_call_tool)
```
### `RequestContext` and `ProgressContext` type parameters simplified
@ -471,12 +471,292 @@ await client.read_resource("test://resource")
await client.read_resource(str(my_any_url))
```
### Lowlevel `Server`: constructor parameters are now keyword-only
All parameters after `name` are now keyword-only. If you were passing `version` or other parameters positionally, use keyword arguments instead:
```python
# Before (v1)
server = Server("my-server", "1.0")
# After (v2)
server = Server("my-server", version="1.0")
```
### Lowlevel `Server`: type parameter reduced from 2 to 1
The `Server` class previously had two type parameters: `Server[LifespanResultT, RequestT]`. The `RequestT` parameter has been removed — handlers now receive typed params directly rather than a generic request type.
```python
# Before (v1)
from typing import Any
from mcp.server.lowlevel.server import Server
server: Server[dict[str, Any], Any] = Server(...)
# After (v2)
from typing import Any
from mcp.server import Server
server: Server[dict[str, Any]] = Server(...)
```
### Lowlevel `Server`: `request_handlers` and `notification_handlers` attributes removed
The public `server.request_handlers` and `server.notification_handlers` dictionaries have been removed. Handler registration is now done exclusively through constructor `on_*` keyword arguments. There is no public API to register handlers after construction.
```python
# Before (v1) — direct dict access
from mcp.types import ListToolsRequest
if ListToolsRequest in server.request_handlers:
...
# After (v2) — no public access to handler dicts
# Use the on_* constructor params to register handlers
server = Server("my-server", on_list_tools=handle_list_tools)
```
### Lowlevel `Server`: decorator-based handlers replaced with constructor `on_*` params
The lowlevel `Server` class no longer uses decorator methods for handler registration. Instead, handlers are passed as `on_*` keyword arguments to the constructor.
**Before (v1):**
```python
from mcp.server.lowlevel.server import Server
server = Server("my-server")
@server.list_tools()
async def handle_list_tools():
return [types.Tool(name="my_tool", description="A tool", inputSchema={})]
@server.call_tool()
async def handle_call_tool(name: str, arguments: dict):
return [types.TextContent(type="text", text=f"Called {name}")]
```
**After (v2):**
```python
from mcp.server import Server, ServerRequestContext
from mcp.types import (
CallToolRequestParams,
CallToolResult,
ListToolsResult,
PaginatedRequestParams,
TextContent,
Tool,
)
async def handle_list_tools(ctx: ServerRequestContext, params: PaginatedRequestParams | None) -> ListToolsResult:
return ListToolsResult(tools=[Tool(name="my_tool", description="A tool", input_schema={})])
async def handle_call_tool(ctx: ServerRequestContext, params: CallToolRequestParams) -> CallToolResult:
return CallToolResult(
content=[TextContent(type="text", text=f"Called {params.name}")],
is_error=False,
)
server = Server("my-server", on_list_tools=handle_list_tools, on_call_tool=handle_call_tool)
```
**Key differences:**
- Handlers receive `(ctx, params)` instead of the full request object or unpacked arguments. `ctx` is a `ServerRequestContext` with `session`, `lifespan_context`, and `experimental` fields (plus `request_id`, `meta`, etc. for request handlers). `params` is the typed request params object.
- Handlers return the full result type (e.g. `ListToolsResult`) rather than unwrapped values (e.g. `list[Tool]`).
- The automatic `jsonschema` input/output validation that the old `call_tool()` decorator performed has been removed. There is no built-in replacement — if you relied on schema validation in the lowlevel server, you will need to validate inputs yourself in your handler.
**Notification handlers:**
```python
from mcp.server import Server, ServerRequestContext
from mcp.types import ProgressNotificationParams
async def handle_progress(ctx: ServerRequestContext, params: ProgressNotificationParams) -> None:
print(f"Progress: {params.progress}/{params.total}")
server = Server("my-server", on_progress=handle_progress)
```
### Lowlevel `Server`: automatic return value wrapping removed
The old decorator-based handlers performed significant automatic wrapping of return values. This magic has been removed — handlers now return fully constructed result types. If you want these conveniences, use `MCPServer` (previously `FastMCP`) instead of the lowlevel `Server`.
**`call_tool()` — structured output wrapping removed:**
The old decorator accepted several return types and auto-wrapped them into `CallToolResult`:
```python
# Before (v1) — returning a dict auto-wrapped into structured_content + JSON TextContent
@server.call_tool()
async def handle(name: str, arguments: dict) -> dict:
return {"temperature": 22.5, "city": "London"}
# Before (v1) — returning a list auto-wrapped into CallToolResult.content
@server.call_tool()
async def handle(name: str, arguments: dict) -> list[TextContent]:
return [TextContent(type="text", text="Done")]
```
```python
# After (v2) — construct the full result yourself
import json
async def handle(ctx: ServerRequestContext, params: CallToolRequestParams) -> CallToolResult:
data = {"temperature": 22.5, "city": "London"}
return CallToolResult(
content=[TextContent(type="text", text=json.dumps(data, indent=2))],
structured_content=data,
)
```
Note: `params.arguments` can be `None` (the old decorator defaulted it to `{}`). Use `params.arguments or {}` to preserve the old behavior.
**`read_resource()` — content type wrapping removed:**
The old decorator auto-wrapped `str` into `TextResourceContents` and `bytes` into `BlobResourceContents` (with base64 encoding), and applied a default mime type of `text/plain`:
```python
# Before (v1) — str/bytes auto-wrapped with mime type defaulting
@server.read_resource()
async def handle(uri: str) -> str:
return "file contents"
@server.read_resource()
async def handle(uri: str) -> bytes:
return b"\x89PNG..."
```
```python
# After (v2) — construct TextResourceContents or BlobResourceContents yourself
import base64
async def handle_read(ctx: ServerRequestContext, params: ReadResourceRequestParams) -> ReadResourceResult:
# Text content
return ReadResourceResult(
contents=[TextResourceContents(uri=str(params.uri), text="file contents", mime_type="text/plain")]
)
async def handle_read(ctx: ServerRequestContext, params: ReadResourceRequestParams) -> ReadResourceResult:
# Binary content — you must base64-encode it yourself
return ReadResourceResult(
contents=[BlobResourceContents(
uri=str(params.uri),
blob=base64.b64encode(b"\x89PNG...").decode("utf-8"),
mime_type="image/png",
)]
)
```
**`list_tools()`, `list_resources()`, `list_prompts()` — list wrapping removed:**
The old decorators accepted bare lists and wrapped them into the result type:
```python
# Before (v1)
@server.list_tools()
async def handle() -> list[Tool]:
return [Tool(name="my_tool", ...)]
# After (v2)
async def handle(ctx: ServerRequestContext, params: PaginatedRequestParams | None) -> ListToolsResult:
return ListToolsResult(tools=[Tool(name="my_tool", ...)])
```
**Using `MCPServer` instead:**
If you prefer the convenience of automatic wrapping, use `MCPServer` which still provides these features through its `@mcp.tool()`, `@mcp.resource()`, and `@mcp.prompt()` decorators. The lowlevel `Server` is intentionally minimal — it provides no magic and gives you full control over the MCP protocol types.
### Lowlevel `Server`: `request_context` property removed
The `server.request_context` property has been removed. Request context is now passed directly to handlers as the first argument (`ctx`). The `request_ctx` module-level contextvar is now an internal implementation detail and should not be relied upon.
**Before (v1):**
```python
from mcp.server.lowlevel.server import request_ctx
@server.call_tool()
async def handle_call_tool(name: str, arguments: dict):
ctx = server.request_context # or request_ctx.get()
await ctx.session.send_log_message(level="info", data="Processing...")
return [types.TextContent(type="text", text="Done")]
```
**After (v2):**
```python
from mcp.server import ServerRequestContext
from mcp.types import CallToolRequestParams, CallToolResult, TextContent
async def handle_call_tool(ctx: ServerRequestContext, params: CallToolRequestParams) -> CallToolResult:
await ctx.session.send_log_message(level="info", data="Processing...")
return CallToolResult(
content=[TextContent(type="text", text="Done")],
is_error=False,
)
```
### `RequestContext`: request-specific fields are now optional
The `RequestContext` class now uses optional fields for request-specific data (`request_id`, `meta`, etc.) so it can be used for both request and notification handlers. In notification handlers, these fields are `None`.
```python
from mcp.server import ServerRequestContext
# request_id, meta, etc. are available in request handlers
# but None in notification handlers
```
### Experimental: task handler decorators removed
The experimental decorator methods on `ExperimentalHandlers` (`@server.experimental.list_tasks()`, `@server.experimental.get_task()`, etc.) have been removed.
Default task handlers are still registered automatically via `server.experimental.enable_tasks()`. Custom handlers can be passed as `on_*` kwargs to override specific defaults.
**Before (v1):**
```python
server = Server("my-server")
server.experimental.enable_tasks()
@server.experimental.get_task()
async def custom_get_task(request: GetTaskRequest) -> GetTaskResult:
...
```
**After (v2):**
```python
from mcp.server import Server, ServerRequestContext
from mcp.types import GetTaskRequestParams, GetTaskResult
async def custom_get_task(ctx: ServerRequestContext, params: GetTaskRequestParams) -> GetTaskResult:
...
server = Server("my-server")
server.experimental.enable_tasks(on_get_task=custom_get_task)
```
## Deprecations
<!-- Add deprecations below -->
## Bug Fixes
### Lowlevel `Server`: `subscribe` capability now correctly reported
Previously, the lowlevel `Server` hardcoded `subscribe=False` in resource capabilities even when a `subscribe_resource()` handler was registered. The `subscribe` capability is now dynamically set to `True` when an `on_subscribe_resource` handler is provided. Clients that previously didn't see `subscribe: true` in capabilities will now see it when a handler is registered, which may change client behavior.
### Extra fields no longer allowed on top-level MCP types
MCP protocol types no longer accept arbitrary extra fields at the top level. This matches the MCP specification which only allows extra fields within `_meta` objects, not on the types themselves.
@ -506,16 +786,16 @@ params = CallToolRequestParams(
The `streamable_http_app()` method is now available directly on the lowlevel `Server` class, not just `MCPServer`. This allows using the streamable HTTP transport without the MCPServer wrapper.
```python
from mcp.server.lowlevel.server import Server
from mcp.server import Server, ServerRequestContext
from mcp.types import ListToolsResult, PaginatedRequestParams
server = Server("my-server")
# Register handlers...
@server.list_tools()
async def list_tools():
return [...]
async def handle_list_tools(ctx: ServerRequestContext, params: PaginatedRequestParams | None) -> ListToolsResult:
return ListToolsResult(tools=[...])
server = Server("my-server", on_list_tools=handle_list_tools)
# Create a Starlette app for streamable HTTP
app = server.streamable_http_app(
streamable_http_path="/mcp",
json_response=False,