ai-station/.venv/lib/python3.12/site-packages/mcp/server/fastmcp/resources/templates.py

119 lines
4.6 KiB
Python

"""Resource template functionality."""
from __future__ import annotations
import inspect
import re
from collections.abc import Callable
from typing import TYPE_CHECKING, Any
from pydantic import BaseModel, Field, validate_call
from mcp.server.fastmcp.resources.types import FunctionResource, Resource
from mcp.server.fastmcp.utilities.context_injection import find_context_parameter, inject_context
from mcp.server.fastmcp.utilities.func_metadata import func_metadata
from mcp.types import Annotations, Icon
if TYPE_CHECKING:
from mcp.server.fastmcp.server import Context
from mcp.server.session import ServerSessionT
from mcp.shared.context import LifespanContextT, RequestT
class ResourceTemplate(BaseModel):
"""A template for dynamically creating resources."""
uri_template: str = Field(description="URI template with parameters (e.g. weather://{city}/current)")
name: str = Field(description="Name of the resource")
title: str | None = Field(description="Human-readable title of the resource", default=None)
description: str | None = Field(description="Description of what the resource does")
mime_type: str = Field(default="text/plain", description="MIME type of the resource content")
icons: list[Icon] | None = Field(default=None, description="Optional list of icons for the resource template")
annotations: Annotations | None = Field(default=None, description="Optional annotations for the resource template")
fn: Callable[..., Any] = Field(exclude=True)
parameters: dict[str, Any] = Field(description="JSON schema for function parameters")
context_kwarg: str | None = Field(None, description="Name of the kwarg that should receive context")
@classmethod
def from_function(
cls,
fn: Callable[..., Any],
uri_template: str,
name: str | None = None,
title: str | None = None,
description: str | None = None,
mime_type: str | None = None,
icons: list[Icon] | None = None,
annotations: Annotations | None = None,
context_kwarg: str | None = None,
) -> ResourceTemplate:
"""Create a template from a function."""
func_name = name or fn.__name__
if func_name == "<lambda>":
raise ValueError("You must provide a name for lambda functions") # pragma: no cover
# Find context parameter if it exists
if context_kwarg is None: # pragma: no branch
context_kwarg = find_context_parameter(fn)
# Get schema from func_metadata, excluding context parameter
func_arg_metadata = func_metadata(
fn,
skip_names=[context_kwarg] if context_kwarg is not None else [],
)
parameters = func_arg_metadata.arg_model.model_json_schema()
# ensure the arguments are properly cast
fn = validate_call(fn)
return cls(
uri_template=uri_template,
name=func_name,
title=title,
description=description or fn.__doc__ or "",
mime_type=mime_type or "text/plain",
icons=icons,
annotations=annotations,
fn=fn,
parameters=parameters,
context_kwarg=context_kwarg,
)
def matches(self, uri: str) -> dict[str, Any] | None:
"""Check if URI matches template and extract parameters."""
# Convert template to regex pattern
pattern = self.uri_template.replace("{", "(?P<").replace("}", ">[^/]+)")
match = re.match(f"^{pattern}$", uri)
if match:
return match.groupdict()
return None
async def create_resource(
self,
uri: str,
params: dict[str, Any],
context: Context[ServerSessionT, LifespanContextT, RequestT] | None = None,
) -> Resource:
"""Create a resource from the template with the given parameters."""
try:
# Add context to params if needed
params = inject_context(self.fn, params, context, self.context_kwarg)
# Call function and check if result is a coroutine
result = self.fn(**params)
if inspect.iscoroutine(result):
result = await result
return FunctionResource(
uri=uri, # type: ignore
name=self.name,
title=self.title,
description=self.description,
mime_type=self.mime_type,
icons=self.icons,
annotations=self.annotations,
fn=lambda: result, # Capture result in closure
)
except Exception as e:
raise ValueError(f"Error creating resource from template: {e}")