Crypto Indicators MCP Server

The Crypto Indicators MCP Server fills a critical gap for AI‑driven trading agents: the ability to compute an extensive suite of technical analysis tools without building custom integrations. By exposing over 50 well‑established indicators and corresponding trading strategies through the Model Context Protocol, it lets developers plug robust market intelligence straight into their conversational AI workflows. This eliminates the need to write boilerplate code for each indicator, ensuring that agents can query real‑time price data and receive actionable signals in a single request.

At its core, the server retrieves market data from a configurable exchange—by default Binance via the library—and runs a modular collection of algorithms. The indicators span trend, momentum, volatility, and volume families, covering classics such as SMA, EMA, MACD, CCI, and PSAR, alongside less common tools like Mass Index or Qstick. Each indicator is packaged as an isolated tool that accepts a symbol, timeframe, and optional parameters, then returns the computed value. In addition to raw indicator outputs, the server offers pre‑built strategies that translate these metrics into discrete trade signals: for SELL, for HOLD, and for BUY. This dual capability allows agents to perform both diagnostic analysis (e.g., “Is the market overbought?”) and prescriptive actions (“Generate a buy signal for BTC‑USDT on 1h”).

Developers can integrate the server into any MCP client—such as Claude Desktop or custom-built assistants—by simply adding a new entry in the client’s configuration. Once connected, an agent can issue natural‑language prompts that map to tool calls: “Calculate the 14‑period RSI for ETH” or “Run the moving‑average crossover strategy on LTC.” The server’s modular design ensures that new indicators or strategies can be added without touching the client code, keeping the ecosystem extensible.

Real‑world use cases abound: automated portfolio managers can query multiple indicators to confirm trend strength before rebalancing; risk‑management bots can monitor volatility metrics and adjust position sizing; or educational agents can demonstrate how a strategy reacts to changing market conditions in real time. Because the server handles data fetching, calculation, and signal generation internally, agents stay lightweight while still delivering sophisticated analytical power.

In summary, the Crypto Indicators MCP Server empowers AI assistants to become full‑featured quantitative traders. By abstracting away data ingestion and algorithmic complexity, it lets developers focus on higher‑level strategy design and user experience, making advanced crypto analysis accessible to anyone who can speak to an AI.