home / mcp / akramsheriff5 mcp server
Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol
Configuration
View docs{
"mcpServers": {
"akramsheriff5-mcp-server": {
"command": "python",
"args": [
"finance/finance_server.py"
]
}
}
}You run lightweight MCP servers that expose focused capabilities through a standardized Model Context Protocol. This guide teaches you how to use the weather-focused server and the finance module, how to install them, and practical tips for getting started quickly with MCP clients.
You connect to each server from your MCP client to access its specific capabilities. For weather-related tasks, you can fetch active weather alerts for a US state, retrieve detailed forecasts for a location, and create support tickets in Freshdesk. For financial insights, you can fetch intraday market data via AlphaVantage, compute moving averages and RSI, and generate trade recommendations based on those indicators.
Prerequisites: Python must be installed on your system. You will also need access to the internet to download dependencies.
git clone https://github.com/your-username/mcp-weather-server.git
cd mcp-weather-serverpython -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activatepip install -r requirements.txtNavigate to the finance module and install its dependencies to ensure all components needed for finance-related MCP tools are available.
cd finance
pip install -r requirements.txtTo run the weather server, start the main entry point from the repository root.
python main.pyTo run the finance server, first change into the finance module directory, then start the finance server script.
cd finance
python finance_server.pyIf you want to run the weather demo server, use the following command.
python weather-demo.pyFetch active weather alerts for a specific US state.
Retrieve detailed weather forecasts for a given location.
Create support tickets in Freshdesk.
Fetch intraday stock market data using the AlphaVantage API.
Calculate short and long period moving averages.
Compute Relative Strength Index (RSI).
Generate comprehensive trade recommendations based on technical indicators.