Integrates with Amazon Q CLI, allowing the MCP server to be configured and used with Amazon Q for command center functionality and mathematical operations.
Leverages Pydantic for data validation and settings management within the MCP server implementation.
Built on Python with specific version requirements (3.11+), using Python's ecosystem for implementing the Mondel Context Protocol server.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Server Bootstrapcalculate the product of 7 and 3 modulo 19"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server Bootstrap: A Template for Building Modular Command Center Servers
MCP Server Bootstrap is a Python-based template for creating modular command center servers using the Mondel Context Protocol (MCP). It provides a structured foundation for building scalable command center applications with support for basic mathematical operations and modular arithmetic functions.
The project implements a modular architecture that combines individual function files into a single server core at runtime. This approach maintains code organization during development while accommodating current MCP SDK limitations regarding modularity. The template provides a foundation for building scalable command center applications with custom functionality.
Repository Structure
mcp_server/ # Main package directory
├── build_mcp.py # Script to combine function modules into core server file
├── functions/ # Directory containing individual function implementations
│ ├── add.py # Addition operation implementation
│ ├── product19.py # Modulo 19 multiplication implementation
│ └── subtract.py # Subtraction operation implementation
├── utils/ # Utility functions and helper modules
│ └── helper.py # Common helper functions
├── pyproject.toml # Project metadata and dependencies
├── requirements.txt # Project dependencies
└── setup.sh # Installation and setup scriptRelated MCP server: MCP Server Python Template
Usage Instructions
Prerequisites
Python 3.11 or higher
Amazon Q CLI installed and configured
pip package manager
Unix-like environment (for setup.sh)
Required packages:
fastmcp >= 1.0.0
pydantic >= 1.10.0
Installation
# Clone the repository
git clone <repository-url>
cd mcp-bootstrap
# Make the setup script executable
chmod +x setup.sh
# The setup script will configure the server for use with Amazon Q CLI
# by creating necessary configuration in $HOME/.aws/amazonq/mcp.json
# Run the setup script
./setup.shQuick Start
Create a new function in the
mcp_server/functionsdirectory:
# mcp_server/functions/example.py
@mcp.tool(
name="example",
description="Example function"
)
def example_function(a: int, b: int) -> int:
return a + bBuild the server:
python mcp_server/build_mcp.pyRun the server:
python mcp_server/core_combined.pyTroubleshooting
Common issues and solutions:
Module Not Found Errors
Error:
ModuleNotFoundError: No module named 'fastmcp'Solution: Ensure you've activated the virtual environment and installed dependencies:
source .venv/bin/activate pip install -r requirements.txt
Build Failures
Error:
FileNotFoundError: core_combined.py not foundSolution: Run the build script from the project root:
python mcp_server/build_mcp.py
Version Compatibility
Error:
Python version X.X is less than required 3.11Solution: Install Python 3.11 or higher and ensure it's in your PATH
Data Flow
The MCP server processes function calls by combining individual function modules into a single core server file, which then handles incoming requests and routes them to the appropriate function implementation.
[Client Request] -> [MCP Server Core] -> [Function Router] -> [Individual Function] -> [Response]
|-> [Function Registry]Component interactions:
The build script combines individual function files into a single core server file
The MCP server initializes with the combined functions
Client requests are received by the server core
Requests are routed to the appropriate function based on the tool name
Functions process the input and return results
The server core formats and sends the response back to the client
Error handling is managed at both the server and function levels
This server cannot be installed
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