What prerequisites are required to run Crypto Price Tracker MCP Server?
You need Docker, a Google Cloud project with the Google Sheets API enabled, and a service account JSON key file placed at a known path.
@RoystonDAlmeida
基本信息
This repository contains files for Crypto Price Tracker MCP Server using Coingecko API.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"crypto-price-tracker-mcp": {
"command": "uv",
"args": [
"pip",
"install",
"-e",
"."
]
}
}
}Get the current watchlist of tracked cryptocurrencies.
Fetch the latest prices for all coins in the watchlist.
A Python-based MCP server that allows users to track cryptocurrency prices, manage a watchlist, and export data to Google Sheets. It is built using the FastMCP framework, designed to run as a Docker container, and integrates with MCP clients like GitHub Copilot via stdio.
Clone the repository, set up a Python virtual environment, install dependencies with uv, obtain Google Sheets API credentials (service account JSON key), build the Docker image, and run the container mounting the credentials file. For MCP client integration (e.g., GitHub Copilot), add a JSON configuration to VSCode’s settings.json specifying the Docker command and credentials path. Interact with the server through natural language prompts; it exposes tools like add_to_watchlist, fetch_prices, and export_to_sheets.
You need Docker, a Google Cloud project with the Google Sheets API enabled, and a service account JSON key file placed at a known path.
The server communicates over stdio (standard input/output), making it compatible with MCP clients like GitHub Copilot.
The README describes building and running the server exclusively as a Docker container; no alternative installation method is provided.
You can export watchlist and price data to a new sheet, share the sheet with a specific user, and analyze performance (highest gain and loss) from a sheet using the `get_sheet_performance_leaders` tool.
The server exposes tools for watchlist management (`get_watchlist`, `add_to_watchlist`, `remove_from_watchlist`), price fetching (`fetch_prices`), Google Sheets export/share (`export_to_sheets`), and performance analysis (`get_sheet_performance_leaders`), plus prompt-generation helpers.
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