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import warnings
from collections.abc import Generator
from contextlib import contextmanager
from contextvars import ContextVar, Token
from dataclasses import dataclass
from mcp import LoggingLevel
from mcp.server.lowlevel.helper_types import ReadResourceContents
from mcp.shared.context import RequestContext
from mcp.types import (
CreateMessageResult,
ImageContent,
ModelHint,
ModelPreferences,
Root,
SamplingMessage,
TextContent,
)
from pydantic.networks import AnyUrl
from starlette.requests import Request
import fastmcp.server.dependencies
from fastmcp.server.server import FastMCP
from fastmcp.utilities.logging import get_logger
logger = get_logger(__name__)
_current_context: ContextVar[Context | None] = ContextVar("context", default=None)
@contextmanager
def set_context(context: Context) -> Generator[Context, None, None]:
token = _current_context.set(context)
try:
yield context
finally:
_current_context.reset(token)
@dataclass
class Context:
"""Context object providing access to MCP capabilities.
This provides a cleaner interface to MCP's RequestContext functionality.
It gets injected into tool and resource functions that request it via type hints.
To use context in a tool function, add a parameter with the Context type annotation:
```python
@server.tool()
def my_tool(x: int, ctx: Context) -> str:
# Log messages to the client
ctx.info(f"Processing {x}")
ctx.debug("Debug info")
ctx.warning("Warning message")
ctx.error("Error message")
# Report progress
ctx.report_progress(50, 100, "Processing")
# Access resources
data = ctx.read_resource("resource://data")
# Get request info
request_id = ctx.request_id
client_id = ctx.client_id
return str(x)
```
The context parameter name can be anything as long as it's annotated with Context.
The context is optional - tools that don't need it can omit the parameter.
"""
def __init__(self, fastmcp: FastMCP):
self.fastmcp = fastmcp
self._tokens: list[Token] = []
def __enter__(self) -> Context:
"""Enter the context manager and set this context as the current context."""
# Always set this context and save the token
token = _current_context.set(self)
self._tokens.append(token)
return self
def __exit__(self, exc_type, exc_val, exc_tb) -> None:
"""Exit the context manager and reset the most recent token."""
if self._tokens:
token = self._tokens.pop()
_current_context.reset(token)
@property
def request_context(self) -> RequestContext:
"""Access to the underlying request context."""
return self.fastmcp._mcp_server.request_context
async def report_progress(
self, progress: float, total: float | None = None, message: str | None = None
) -> None:
"""Report progress for the current operation.
Args:
progress: Current progress value e.g. 24
total: Optional total value e.g. 100
"""
progress_token = (
self.request_context.meta.progressToken
if self.request_context.meta
else None
)
if progress_token is None:
return
await self.request_context.session.send_progress_notification(
progress_token=progress_token,
progress=progress,
total=total,
message=message,
)
async def read_resource(self, uri: str | AnyUrl) -> list[ReadResourceContents]:
"""Read a resource by URI.
Args:
uri: Resource URI to read
Returns:
The resource content as either text or bytes
"""
assert self.fastmcp is not None, "Context is not available outside of a request"
return await self.fastmcp._mcp_read_resource(uri)
async def log(
self,
message: str,
level: LoggingLevel | None = None,
logger_name: str | None = None,
) -> None:
"""Send a log message to the client.
Args:
message: Log message
level: Optional log level. One of "debug", "info", "notice", "warning", "error", "critical",
"alert", or "emergency". Default is "info".
logger_name: Optional logger name
"""
if level is None:
level = "info"
await self.request_context.session.send_log_message(
level=level, data=message, logger=logger_name
)
@property
def client_id(self) -> str | None:
"""Get the client ID if available."""
return (
getattr(self.request_context.meta, "client_id", None)
if self.request_context.meta
else None
)
@property
def request_id(self) -> str:
"""Get the unique ID for this request."""
return str(self.request_context.request_id)
@property
def session(self):
"""Access to the underlying session for advanced usage."""
return self.request_context.session
# Convenience methods for common log levels
async def debug(self, message: str, logger_name: str | None = None) -> None:
"""Send a debug log message."""
await self.log(level="debug", message=message, logger_name=logger_name)
async def info(self, message: str, logger_name: str | None = None) -> None:
"""Send an info log message."""
await self.log(level="info", message=message, logger_name=logger_name)
async def warning(self, message: str, logger_name: str | None = None) -> None:
"""Send a warning log message."""
await self.log(level="warning", message=message, logger_name=logger_name)
async def error(self, message: str, logger_name: str | None = None) -> None:
"""Send an error log message."""
await self.log(level="error", message=message, logger_name=logger_name)
async def list_roots(self) -> list[Root]:
"""List the roots available to the server, as indicated by the client."""
result = await self.request_context.session.list_roots()
return result.roots
async def sample(
self,
messages: str | list[str | SamplingMessage],
system_prompt: str | None = None,
temperature: float | None = None,
max_tokens: int | None = None,
model_preferences: ModelPreferences | str | list[str] | None = None,
) -> TextContent | ImageContent:
"""
Send a sampling request to the client and await the response.
Call this method at any time to have the server request an LLM
completion from the client. The client must be appropriately configured,
or the request will error.
"""
if max_tokens is None:
max_tokens = 512
if isinstance(messages, str):
sampling_messages = [
SamplingMessage(
content=TextContent(text=messages, type="text"), role="user"
)
]
elif isinstance(messages, list):
sampling_messages = [
SamplingMessage(content=TextContent(text=m, type="text"), role="user")
if isinstance(m, str)
else m
for m in messages
]
result: CreateMessageResult = await self.request_context.session.create_message(
messages=sampling_messages,
system_prompt=system_prompt,
temperature=temperature,
max_tokens=max_tokens,
model_preferences=self._parse_model_preferences(model_preferences),
)
return result.content
def get_http_request(self) -> Request:
"""Get the active starlette request."""
# Deprecation warning, added in FastMCP 2.2.11
warnings.warn(
"Context.get_http_request() is deprecated and will be removed in a future version. "
"Use get_http_request() from fastmcp.server.dependencies instead. "
"See https://gofastmcp.com/patterns/http-requests for more details.",
DeprecationWarning,
stacklevel=2,
)
return fastmcp.server.dependencies.get_http_request()
def _parse_model_preferences(
self, model_preferences: ModelPreferences | str | list[str] | None
) -> ModelPreferences | None:
"""
Validates and converts user input for model_preferences into a ModelPreferences object.
Args:
model_preferences (ModelPreferences | str | list[str] | None):
The model preferences to use. Accepts:
- ModelPreferences (returns as-is)
- str (single model hint)
- list[str] (multiple model hints)
- None (no preferences)
Returns:
ModelPreferences | None: The parsed ModelPreferences object, or None if not provided.
Raises:
ValueError: If the input is not a supported type or contains invalid values.
"""
if model_preferences is None:
return None
elif isinstance(model_preferences, ModelPreferences):
return model_preferences
elif isinstance(model_preferences, str):
# Single model hint
return ModelPreferences(hints=[ModelHint(name=model_preferences)])
elif isinstance(model_preferences, list):
# List of model hints (strings)
if not all(isinstance(h, str) for h in model_preferences):
raise ValueError(
"All elements of model_preferences list must be"
" strings (model name hints)."
)
return ModelPreferences(
hints=[ModelHint(name=h) for h in model_preferences]
)
else:
raise ValueError(
"model_preferences must be one of: ModelPreferences, str, list[str], or None."
)
|