mirror of
https://github.com/aljazceru/mcp-python-sdk.git
synced 2025-12-19 14:54:24 +01:00
Update types for spec changes
This commit is contained in:
Justin Spahr-Summers
@@ -1,12 +1,12 @@
|
||||
from typing import Any, Generic, Literal, TypeVar
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, RootModel
|
||||
from pydantic import BaseModel, ConfigDict, FileUrl, RootModel
|
||||
from pydantic.networks import AnyUrl
|
||||
|
||||
"""
|
||||
Model Context Protocol bindings for Python
|
||||
|
||||
These bindings were generated from https://github.com/anthropic-experimental/mcp-spec,
|
||||
These bindings were generated from https://github.com/modelcontextprotocol/specification,
|
||||
using Claude, with a prompt something like the following:
|
||||
|
||||
Generate idiomatic Python bindings for this schema for MCP, or the "Model Context
|
||||
@@ -21,7 +21,7 @@ for reference.
|
||||
not separate types in the schema.
|
||||
"""
|
||||
|
||||
LATEST_PROTOCOL_VERSION = "2024-10-07"
|
||||
LATEST_PROTOCOL_VERSION = "2024-11-05"
|
||||
|
||||
ProgressToken = str | int
|
||||
Cursor = str
|
||||
@@ -191,6 +191,8 @@ class ClientCapabilities(BaseModel):
|
||||
"""Experimental, non-standard capabilities that the client supports."""
|
||||
sampling: dict[str, Any] | None = None
|
||||
"""Present if the client supports sampling from an LLM."""
|
||||
roots: dict[str, Any] | None = None
|
||||
"""Present if the client supports listing roots."""
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
|
||||
@@ -556,12 +558,33 @@ class SamplingMessage(BaseModel):
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
|
||||
class EmbeddedResource(BaseModel):
|
||||
"""
|
||||
The contents of a resource, embedded into a prompt or tool call result.
|
||||
|
||||
It is up to the client how best to render embedded resources for the benefit
|
||||
of the LLM and/or the user.
|
||||
"""
|
||||
|
||||
type: Literal["resource"]
|
||||
resource: TextResourceContents | BlobResourceContents
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
|
||||
class PromptMessage(BaseModel):
|
||||
"""Describes a message returned as part of a prompt."""
|
||||
|
||||
role: Role
|
||||
content: TextContent | ImageContent | EmbeddedResource
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
|
||||
class GetPromptResult(Result):
|
||||
"""The server's response to a prompts/get request from the client."""
|
||||
|
||||
description: str | None = None
|
||||
"""An optional description for the prompt."""
|
||||
messages: list[SamplingMessage]
|
||||
messages: list[PromptMessage]
|
||||
|
||||
|
||||
class PromptListChangedNotification(Notification):
|
||||
@@ -617,7 +640,8 @@ class CallToolRequest(Request):
|
||||
class CallToolResult(Result):
|
||||
"""The server's response to a tool call."""
|
||||
|
||||
toolResult: Any
|
||||
content: list[TextContent | ImageContent | EmbeddedResource]
|
||||
isError: bool
|
||||
|
||||
|
||||
class ToolListChangedNotification(Notification):
|
||||
@@ -630,7 +654,7 @@ class ToolListChangedNotification(Notification):
|
||||
params: NotificationParams | None = None
|
||||
|
||||
|
||||
LoggingLevel = Literal["debug", "info", "warning", "error"]
|
||||
LoggingLevel = Literal["debug", "info", "notice", "warning", "error", "critical", "alert", "emergency"]
|
||||
|
||||
|
||||
class SetLevelRequestParams(RequestParams):
|
||||
@@ -673,10 +697,71 @@ class LoggingMessageNotification(Notification):
|
||||
IncludeContext = Literal["none", "thisServer", "allServers"]
|
||||
|
||||
|
||||
class ModelHint(BaseModel):
|
||||
"""Hints to use for model selection."""
|
||||
|
||||
name: str | None = None
|
||||
"""A hint for a model name."""
|
||||
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
|
||||
class ModelPreferences(BaseModel):
|
||||
"""
|
||||
The server's preferences for model selection, requested of the client during sampling.
|
||||
|
||||
Because LLMs can vary along multiple dimensions, choosing the "best" model is
|
||||
rarely straightforward. Different models excel in different areas—some are
|
||||
faster but less capable, others are more capable but more expensive, and so
|
||||
on. This interface allows servers to express their priorities across multiple
|
||||
dimensions to help clients make an appropriate selection for their use case.
|
||||
|
||||
These preferences are always advisory. The client MAY ignore them. It is also
|
||||
up to the client to decide how to interpret these preferences and how to
|
||||
balance them against other considerations.
|
||||
"""
|
||||
|
||||
hints: list[ModelHint] | None = None
|
||||
"""
|
||||
Optional hints to use for model selection.
|
||||
|
||||
If multiple hints are specified, the client MUST evaluate them in order
|
||||
(such that the first match is taken).
|
||||
|
||||
The client SHOULD prioritize these hints over the numeric priorities, but
|
||||
MAY still use the priorities to select from ambiguous matches.
|
||||
"""
|
||||
|
||||
costPriority: float | None = None
|
||||
"""
|
||||
How much to prioritize cost when selecting a model. A value of 0 means cost
|
||||
is not important, while a value of 1 means cost is the most important
|
||||
factor.
|
||||
"""
|
||||
|
||||
speedPriority: float | None = None
|
||||
"""
|
||||
How much to prioritize sampling speed (latency) when selecting a model. A
|
||||
value of 0 means speed is not important, while a value of 1 means speed is
|
||||
the most important factor.
|
||||
"""
|
||||
|
||||
intelligencePriority: float | None = None
|
||||
"""
|
||||
How much to prioritize intelligence and capabilities when selecting a
|
||||
model. A value of 0 means intelligence is not important, while a value of 1
|
||||
means intelligence is the most important factor.
|
||||
"""
|
||||
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
|
||||
class CreateMessageRequestParams(RequestParams):
|
||||
"""Parameters for creating a message."""
|
||||
|
||||
messages: list[SamplingMessage]
|
||||
modelPreferences: ModelPreferences | None = None
|
||||
"""The server's preferences for which model to select. The client MAY ignore these preferences."""
|
||||
systemPrompt: str | None = None
|
||||
"""An optional system prompt the server wants to use for sampling."""
|
||||
includeContext: IncludeContext | None = None
|
||||
@@ -700,7 +785,7 @@ class CreateMessageRequest(Request):
|
||||
params: CreateMessageRequestParams
|
||||
|
||||
|
||||
StopReason = Literal["endTurn", "stopSequence", "maxTokens"]
|
||||
StopReason = Literal["endTurn", "stopSequence", "maxTokens"] | str
|
||||
|
||||
|
||||
class CreateMessageResult(Result):
|
||||
@@ -710,8 +795,8 @@ class CreateMessageResult(Result):
|
||||
content: TextContent | ImageContent
|
||||
model: str
|
||||
"""The name of the model that generated the message."""
|
||||
stopReason: StopReason
|
||||
"""The reason why sampling stopped."""
|
||||
stopReason: StopReason | None = None
|
||||
"""The reason why sampling stopped, if known."""
|
||||
|
||||
|
||||
class ResourceReference(BaseModel):
|
||||
@@ -781,6 +866,60 @@ class CompleteResult(Result):
|
||||
completion: Completion
|
||||
|
||||
|
||||
class ListRootsRequest(Request):
|
||||
"""
|
||||
Sent from the server to request a list of root URIs from the client. Roots allow
|
||||
servers to ask for specific directories or files to operate on. A common example
|
||||
for roots is providing a set of repositories or directories a server should operate
|
||||
on.
|
||||
|
||||
This request is typically used when the server needs to understand the file system
|
||||
structure or access specific locations that the client has permission to read from.
|
||||
"""
|
||||
|
||||
method: Literal["roots/list"]
|
||||
params: RequestParams | None = None
|
||||
|
||||
|
||||
class Root(BaseModel):
|
||||
"""Represents a root directory or file that the server can operate on."""
|
||||
|
||||
uri: FileUrl
|
||||
"""
|
||||
The URI identifying the root. This *must* start with file:// for now.
|
||||
This restriction may be relaxed in future versions of the protocol to allow
|
||||
other URI schemes.
|
||||
"""
|
||||
name: str | None = None
|
||||
"""
|
||||
An optional name for the root. This can be used to provide a human-readable
|
||||
identifier for the root, which may be useful for display purposes or for
|
||||
referencing the root in other parts of the application.
|
||||
"""
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
|
||||
class ListRootsResult(Result):
|
||||
"""
|
||||
The client's response to a roots/list request from the server.
|
||||
This result contains an array of Root objects, each representing a root directory
|
||||
or file that the server can operate on.
|
||||
"""
|
||||
|
||||
roots: list[Root]
|
||||
|
||||
|
||||
class RootsListChangedNotification(Notification):
|
||||
"""
|
||||
A notification from the client to the server, informing it that the list of roots has changed.
|
||||
This notification should be sent whenever the client adds, removes, or modifies any root.
|
||||
The server should then request an updated list of roots using the ListRootsRequest.
|
||||
"""
|
||||
|
||||
method: Literal["notifications/roots/list_changed"]
|
||||
params: NotificationParams | None = None
|
||||
|
||||
|
||||
class ClientRequest(
|
||||
RootModel[
|
||||
PingRequest
|
||||
@@ -801,15 +940,15 @@ class ClientRequest(
|
||||
pass
|
||||
|
||||
|
||||
class ClientNotification(RootModel[ProgressNotification | InitializedNotification]):
|
||||
class ClientNotification(RootModel[ProgressNotification | InitializedNotification | RootsListChangedNotification]):
|
||||
pass
|
||||
|
||||
|
||||
class ClientResult(RootModel[EmptyResult | CreateMessageResult]):
|
||||
class ClientResult(RootModel[EmptyResult | CreateMessageResult | ListRootsResult]):
|
||||
pass
|
||||
|
||||
|
||||
class ServerRequest(RootModel[PingRequest | CreateMessageRequest]):
|
||||
class ServerRequest(RootModel[PingRequest | CreateMessageRequest | ListRootsRequest]):
|
||||
pass
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user