Python Base SDK for interacting with the Toolbox service, designed to seamlessly integrate the functionalities of the MCP Toolbox into your Gen AI applications by allowing you to load and use tools defined in the service as standard Python functions. It is actively maintained by Google and released version 1.0.0 on March 25, 2026, with related SDKs and the core Toolbox service undergoing rapid development and frequent updates.
pip install toolbox-coreVerified import paths — ran on the pinned version, not inferred.
This quickstart demonstrates how to initialize the `ToolboxClient`, connect to a running MCP Toolbox service (requires a locally or remotely deployed server), and load and invoke a predefined tool, such as 'get_weather'. Make sure the `TOOLBOX_SERVICE_URL` environment variable is set or the default URL is correct.
Regularly check the main MCP Toolbox GitHub repository's CHANGELOG for updates and migration guides. Update `toolbox-core` and adapt client code as necessary.
Verify the MCP Toolbox server is running and its URL (`http://127.0.0.1:5000` by default in examples) is correctly configured in your client code or via the `TOOLBOX_SERVICE_URL` environment variable. Consult the MCP Toolbox Server Getting Started Guide for deployment instructions.
Ensure the tool name passed to `load_tool()` (e.g., 'get_weather') exactly matches a tool configured on your running Toolbox server. Review the server's `tools.yaml` configuration or equivalent definition for correct tool names and parameter schemas.
Ensure the MCP Toolbox server application is actively running. Verify the `ToolboxClient` initialization URL (e.g., `http://127.0.0.1:5000`) matches the server's actual host and port. Check local firewall settings if connecting to a remote server.
Confirm the exact name of the tool you are trying to load (e.g., 'get_weather') is correctly spelled and configured on your MCP Toolbox server. Review the server's tool definitions to ensure the tool is available.
Consult the documentation or schema for the specific tool you are invoking on the MCP Toolbox server. Ensure that the keyword arguments and their types passed in your Python code (e.g., `location="London"`) align perfectly with the tool's definition.