Crypto Price Tracker MCP Server

Crypto Price Tracker MCP Server

The Crypto Price Tracker MCP Server solves a common pain point for developers building AI‑powered financial tools: obtaining up‑to‑date cryptocurrency data, maintaining a personalized watchlist, and sharing insights without writing boilerplate code. By exposing its functionality through the Model Context Protocol (MCP), the server lets AI assistants—such as Claude or Copilot—to act as first‑class clients, issuing commands and receiving structured responses in a single, lightweight interaction channel.

At its core, the server provides three intertwined capabilities. First, watchlist management lets users add or remove coins and retrieve the current list with a single tool call. Second, price tracking pulls live market data from CoinGecko’s public API and returns the latest prices for every item in the watchlist. Finally, Google Sheets integration enables users to export that data, share a spreadsheet with collaborators, and even compute performance metrics (e.g., highest gain or loss) directly from the sheet. All of these operations are wrapped in MCP tools and prompts, so an AI assistant can orchestrate complex workflows—such as “update my watchlist, fetch prices, and email the results to a stakeholder”—with minimal effort.

Key features include:

• Declarative tool definitions that expose CRUD operations for the watchlist and price retrieval, making it trivial to compose new actions in an AI prompt.
• Stateless HTTP interface built on FastMCP, allowing the server to run in any containerized environment without side‑effects.
• Built‑in Google Sheets API support that handles authentication via a service account JSON key, writes tabular data, and shares the sheet on demand.
• Extensible prompt templates that let developers tailor natural‑language interactions to their domain, such as generating investment summaries or alerts.

Real‑world scenarios benefit from this server in several ways. A fintech startup can let its AI assistant maintain an internal portfolio tracker, automatically updating prices and pushing daily summaries to a shared Google Sheet. A research analyst can query the watchlist, retrieve the latest market data, and have the assistant generate a markdown report with performance charts. Even hobbyists building personal dashboards can rely on the MCP interface to fetch data without writing HTTP clients.

Integration into AI workflows is straightforward: an MCP‑enabled client sends a JSON payload describing the desired tool (e.g., ) and its arguments. The server processes the request, performs the action (fetching data from CoinGecko or writing to Google Sheets), and returns a structured response. The AI assistant can then use that response in subsequent prompts, enabling multi‑step reasoning and automation.

What sets this MCP server apart is its complete end‑to‑end pipeline—from data ingestion to collaboration—wrapped in a single, containerized service that communicates over standard input/output. Developers who already use MCP for other services can add cryptocurrency tracking to their ecosystem with minimal friction, leveraging the same tooling and security model that powers their existing AI assistants.