Added new --url parameter to the mcp command to run an MCP server for a remote host running MultiViewer.

MCP Server

New to this release is a Model Context Protocol (MCP) server for MultiViewer enabling AI agents to control your setup.

To launch the MCP server, simply mvf1-cli mcp.

To add to an agentic framework like PydanticAI, use their affordance for a stdio MCP server. For example:

from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStdio

server = MCPServerStdio(  
    'mvf1-cli',
    args=[
        'mcp'
    ]
)
agent = Agent('openai:gpt-4o', mcp_servers=[server])

BREAKING CHANGE

The breaking change for this release is dropping support for Python versions <3.10, as a result of the new dependency fastmcp.

Added ability to set_driver_header_mode for driver feeds - users can choose between NONE, DRIVER_HEADER that shows the driver team an TLA, or OBC_LIVE_TIMING for current data.

First release of this Python module and command line interface for MultiViewer for F1.

Featured in this release:

• Command line interface for controlling MultiViewer for F1. Great for integration peripherals like the Elgato Streamdeck with MVF1.
• Pythonic interface for controlling MultiViewer For F1 from your code. No GraphQL needed!
• Type hints
• Full documentation
• Test coverage