MCP Tool Server Template
@mibexx
About MCP Tool Server Template
No overview available yet
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mbxai-mcp-server-template": {
"command": "uv",
"args": [
"venv"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is MCP Tool Server Template?
It is a cookiecutter template for scaffolding Model Context Protocol (MCP) tool servers using FastAPI, uv, and Docker. It is intended for developers who want to quickly set up an MCP server with modern Python tooling and a sample weather tool.
How to use MCP Tool Server Template?
Use cookiecutter to generate a new project: cookiecutter gh:mibexx/mbxai-mcp-server-template and answer the prompts for project name, slug, etc. Then navigate into the generated directory and run uv run service to start the server locally, or use docker-compose up -d for containerized execution.
Key features of MCP Tool Server Template
- FastAPI-based REST server with MCP tool support
- Sample weather tool for quick prototyping
- Modern Python tooling: uv, ruff, mypy
- Type hints and comprehensive testing
- Docker and Docker Compose support
- Kubernetes deployment configuration
Use cases of MCP Tool Server Template
- Quickly bootstrap a new MCP tool server project
- Prototype MCP tools with a built-in weather example
- Develop and test MCP servers using modern Python stack
- Containerize and deploy MCP servers via Docker or Kubernetes
- Provide a consistent project structure for team collaboration
FAQ from MCP Tool Server Template
What dependencies are required to use this template?
The template requires Python 3.12 or higher, the uv package manager, and cookiecutter version 2.5.0 or higher.
How do I create a new MCP server project?
Run cookiecutter gh:mibexx/mbxai-mcp-server-template and follow the interactive prompts to configure your project.
How can I run the generated server locally?
Navigate into the generated project directory, create a virtual environment with uv venv, activate it, install the package with uv pip install -e ., then run uv run service.
What deployment options are provided?
The template includes Docker and Docker Compose configurations for containerized deployment, as well as Kubernetes deployment files in the kubernetes/ directory.
Is there a sample tool included to get started?
Yes, the template includes a sample weather tool implementation located at src/your_package/project/weather.py.
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