Tokens MCP

The Tokens MCP server acts as a bridge between AI assistants and the TokenMetrics API, a comprehensive provider of cryptocurrency market data. By exposing token prices, historical charts, and trading‑strategy backtesting tools through the Model Context Protocol (MCP), it eliminates the need for developers to write custom API wrappers or handle authentication manually. Instead, an AI assistant can issue high‑level requests—such as “generate a moving‑average crossover strategy for Bitcoin” or “compare token performance over the last quarter”—and receive structured, ready‑to‑use responses directly from the server.

For developers building algorithmic trading bots or conducting market research, this MCP offers several key advantages. First, it centralizes API access: a single server instance manages all TokenMetrics calls, ensuring consistent credentials and rate‑limit handling. Second, it enriches data with built‑in chart generation utilities; AI agents can request visual performance metrics without leaving the MCP environment. Third, the server supports backtesting out of the box, allowing AI assistants to evaluate strategy profitability across multiple timeframes and assets before deployment. These capabilities reduce development overhead, shorten iteration cycles, and enable rapid prototyping of complex trading logic.

Typical use cases include automated portfolio management where an AI assistant continually monitors token volatility and rebalances holdings, or data‑driven research projects that require comparative analysis of emerging altcoins. Because the server is MCP‑compatible, it integrates seamlessly into IDEs such as Cursor, which can invoke its tools directly from the editor or through conversational prompts. This tight integration streamlines workflows: a developer can ask the AI to “plot the 50‑day moving average for Ethereum” and instantly receive a chart rendered by the server, all within the same development environment.

What sets Tokens MCP apart is its focus on crypto‑specific features. Unlike generic financial APIs, it exposes domain‑native concepts such as token symbols, exchange listings, and historical market cap data. The server’s modular design—separate modules for chart utilities, API inspection, and cache management—makes it easy to extend or customize. Developers can add new strategy templates or plug in alternative data sources without altering the core MCP interface, ensuring long‑term maintainability. In short, Tokens MCP delivers a ready‑made, AI‑friendly gateway to token metrics that accelerates both research and production trading workflows.