MCP Auto Register is a Python package designed to streamline the process of registering functions and classes from Python packages with FastMCP instances. This tool automates the registration process, significantly reducing manual configuration and boosting developer efficiency. It offers two primary functions: register_functions_from_package for registering functions and register_classes_from_package for registering classes.

By automating the registration of Python packages, MCP Auto Register facilitates seamless interaction between AI models and external data sources or services. Developers can easily expose functionalities from existing Python libraries to their AI models through FastMCP. This simplifies integration, reduces boilerplate code, and accelerates the development lifecycle. The package is installed via pip and integrates directly with FastMCP, making it a valuable asset for developers building AI-powered applications.

Automated Function Registration

mcp_auto_register automates the process of registering functions from Python packages to a FastMCP instance. This eliminates the need for manual configuration, significantly reducing the boilerplate code required to expose functions as MCP resources. The function register_functions_from_package scans the specified package, filters functions based on user-defined criteria (e.g., function names), and registers them with the provided FastMCP instance. This streamlined approach accelerates development and simplifies the integration of existing Python code into the MCP ecosystem. For example, a data scientist can quickly expose statistical functions from scipy.stats via MCP, allowing AI models to access these functions as external resources. This function uses Python's introspection capabilities to dynamically discover and register functions.

Automated Class Registration

Similar to function registration, mcp_auto_register also automates the registration of classes from Python packages. The register_classes_from_package function iterates through the specified package, identifies classes, and registers them with the FastMCP instance. This feature is particularly useful for exposing complex functionalities encapsulated within classes as MCP resources. A key aspect is the ability to apply a wrapper function to each class before registration. This allows for customization of the class interface, adapting it to the specific requirements of the MCP environment. For instance, when integrating with the nba_api, a wrapper function can be used to extract and format the relevant data from the API's endpoint classes, ensuring a consistent and easily consumable interface for AI models. This involves using inspect module to analyze class constructors and create appropriate function signatures.

Simplified MCP Integration

mcp_auto_register simplifies the integration of Python packages with the MCP ecosystem by providing a high-level interface for registering functions and classes. This abstraction reduces the complexity of interacting with the FastMCP server, allowing developers to focus on the core logic of their AI models and external resources. By automating the registration process, mcp_auto_register promotes code reusability and reduces the potential for errors associated with manual configuration. The tool acts as a bridge, seamlessly connecting Python-based functionalities with the standardized MCP framework. For example, instead of manually defining each function and its corresponding MCP endpoint, developers can use mcp_auto_register to automatically expose an entire library of functions with a few lines of code. This simplification is crucial for rapid prototyping and deployment of AI solutions within the MCP ecosystem.