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An MCP server that tracks real-time data for major crypto-related stocks.
Configuration
View docs{
"mcpServers": {
"kukapay-crypto-stocks-mcp": {
"command": "uv",
"args": [
"--directory",
"/path/to/crypto-stocks-mcp",
"run",
"main.py"
]
}
}
}You can run and interact with a real-time Crypto Stocks MCP Server that tracks crypto-related stock data, including lists, prices, and historical data. It lets you query current values and trends to help AI agents analyze investment opportunities.
You will connect to the Crypto Stocks MCP Server using an MCP-compatible client. The server exposes capabilities to list crypto-related stocks, fetch real-time prices, retrieve historical data, and generate natural language prompts for stock queries. Use these capabilities to build interactive prompts that retrieve up-to-date information and historical context for decision making.
Prerequisites: you need Python 3.10 or higher. Install a runtime tool for MCP integration such as uv (recommended) or use pip for dependency management.
Step 1: Clone the project directory.
git clone https://github.com/kukapay/crypto-stocks-mcp.git
cd crypto-stocks-mcpStep 2: Install dependencies using uv (recommended).
uv syncStep 3: Install to Claude Desktop or your MCP client. Run the server with the following command.
uv run mcp install main.py --name "Crypto Stocks"Configuration example you can use for reference in your MCP setup. This config defines a single MCP server named for Crypto Stocks and uses uv to execute the server from your local path.
{
"mcpServers": {
"Crypto Stocks": {
"command": "uv",
"args": [ "--directory", "/path/to/crypto-stocks-mcp", "run", "main.py" ]
}
}
}Notes and practical tips to get started quickly.
Examples of interactions you can run after the server is up.
Retrieve a table of crypto-related stocks with ticker symbols and company names.
Fetch the latest price for a specified stock ticker, including price and timestamp.
Access historical stock prices and trading volumes for a specified number of days.
Generate and execute natural language prompts to query stock information.