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fastmcp.utilities.mcp_server_config.v1.mcp_server_config

FastMCP Configuration File Support. This module provides support for fastmcp.json configuration files that allow users to specify server settings in a declarative format instead of using command-line arguments.

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Functions

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generate_schema 

generate_schema(output_path: Path | str | None = None) -> dict[str, Any] | None
Generate JSON schema for fastmcp.json files. This is used to create the schema file that IDEs can use for validation and auto-completion. Args:
  • output_path: Optional path to write the schema to. If provided, writes the schema and returns None. If not provided, returns the schema as a dictionary.
Returns:
  • JSON schema as a dictionary if output_path is None, otherwise None

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Classes

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Deployment

Configuration for server deployment and runtime settings. Methods:

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apply_runtime_settings 

apply_runtime_settings(self, config_path: Path | None = None) -> None
Apply runtime settings like environment variables and working directory. Args:
  • config_path: Path to config file for resolving relative paths
Environment variables support interpolation with VARNAMEsyntax.Forexample:"APIURL":"https://api.{VAR_NAME} syntax. For example: "API_URL": "https://api..example.com” will substitute the value of the ENVIRONMENT variable at runtime.

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MCPServerConfig

Configuration for a FastMCP server. This configuration file allows you to specify all settings needed to run a FastMCP server in a declarative format. Methods:

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validate_source 

validate_source(cls, v: dict | Source) -> SourceType
Validate and convert source to proper format. Supports:
  • Dict format: {"path": "server.py", "entrypoint": "app"}
  • FileSystemSource instance (passed through)
No string parsing happens here - that’s only at CLI boundaries. MCPServerConfig works only with properly typed objects.

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validate_environment 

validate_environment(cls, v: dict | Any) -> EnvironmentType
Ensure environment has a type field for discrimination. For backward compatibility, if no type is specified, default to “uv”.

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validate_deployment 

validate_deployment(cls, v: dict | Deployment) -> Deployment
Validate and convert deployment to Deployment. Accepts:
  • Deployment instance
  • dict that can be converted to Deployment

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from_file 

from_file(cls, file_path: Path) -> MCPServerConfig
Load configuration from a JSON file. Args:
  • file_path: Path to the configuration file
Returns:
  • MCPServerConfig instance
Raises:
  • FileNotFoundError: If the file doesn’t exist
  • json.JSONDecodeError: If the file is not valid JSON
  • pydantic.ValidationError: If the configuration is invalid

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from_cli_args 

from_cli_args(cls, source: FileSystemSource, transport: Literal['stdio', 'http', 'sse', 'streamable-http'] | None = None, host: str | None = None, port: int | None = None, path: str | None = None, log_level: Literal['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'] | None = None, python: str | None = None, dependencies: list[str] | None = None, requirements: str | None = None, project: str | None = None, editable: str | None = None, env: dict[str, str] | None = None, cwd: str | None = None, args: list[str] | None = None) -> MCPServerConfig
Create a config from CLI arguments. This allows us to have a single code path where everything goes through a config object. Args:
  • source: Server source (FileSystemSource instance)
  • transport: Transport protocol
  • host: Host for HTTP transport
  • port: Port for HTTP transport
  • path: URL path for server
  • log_level: Logging level
  • python: Python version
  • dependencies: Python packages to install
  • requirements: Path to requirements file
  • project: Path to project directory
  • editable: Path to install in editable mode
  • env: Environment variables
  • cwd: Working directory
  • args: Server arguments
Returns:
  • MCPServerConfig instance

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find_config 

find_config(cls, start_path: Path | None = None) -> Path | None
Find a fastmcp.json file in the specified directory. Args:
  • start_path: Directory to look in (defaults to current directory)
Returns:
  • Path to the configuration file, or None if not found

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prepare 

prepare(self, skip_source: bool = False, output_dir: Path | None = None) -> None
Prepare environment and source for execution. When output_dir is provided, creates a persistent uv project. When output_dir is None, does ephemeral caching (for backwards compatibility). Args:
  • skip_source: Skip source preparation if True
  • output_dir: Directory to create the persistent uv project in (optional)

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prepare_environment 

prepare_environment(self, output_dir: Path | None = None) -> None
Prepare the Python environment. Args:
  • output_dir: If provided, creates a persistent uv project in this directory. If None, just populates uv’s cache for ephemeral use.
Delegates to the environment’s prepare() method

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prepare_source 

prepare_source(self) -> None
Prepare the source for loading. Delegates to the source’s prepare() method.

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run_server 

run_server(self, **kwargs: Any) -> None
Load and run the server with this configuration. Args:
  • **kwargs: Additional arguments to pass to server.run_async() These override config settings
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