Token Metrics MCP Server

Token Metrics MCP Server Overview

Token Metrics provides a dedicated Model Context Protocol (MCP) server that exposes the full breadth of its cryptocurrency data, analytics, and trading intelligence to AI assistants. The server bridges the gap between raw market feeds and intelligent agents by offering a curated set of tools that return real‑time prices, technical indicators, sentiment scores, and AI‑generated trading signals. Developers can embed these capabilities directly into conversational workflows, allowing agents to answer market questions, generate trade recommendations, or run scenario analyses without leaving the chat interface.

The core value of this MCP lies in its ability to transform complex crypto analytics into simple, callable functions. Each tool encapsulates a specific data retrieval or analytical operation—such as fetching hourly OHLCV bars, calculating support and resistance levels, or grading a token’s suitability for short‑term trading versus long‑term investment. By abstracting away the underlying API calls, developers can focus on orchestrating logic rather than handling authentication or pagination. This abstraction is especially beneficial for agents that need to synthesize multiple data points, combine them with user intent, and produce actionable insights in real time.

Key features include:

• Real‑time market data: Current prices, volume, and market cap for thousands of tokens.
• AI‑generated trading signals: Long/short recommendations derived from proprietary models.
• Advanced price forecasting: Scenario analysis and predictive metrics for informed decision‑making.
• Technical analysis tools: Support/resistance levels, correlation matrices, and trend indicators.
• Sentiment and market intelligence: Comprehensive sentiment scores and macro‑market insights.

Typical use cases span portfolio management, automated trading bots, educational platforms, and research dashboards. An AI assistant can answer questions like “Show me the top 5 tokens with a bullish signal today” or “What is the support level for BTC/USD?” and return structured data that can be rendered as charts or fed into downstream decision engines. In a trading environment, the server’s grading functions help agents filter assets based on risk appetite or investment horizon.

Integration is straightforward: developers add the MCP server to their client configuration, either via a hosted HTTP endpoint or a local installation. Once registered, the agent can invoke any of the exposed tools through function calls, receiving JSON payloads that can be parsed and acted upon. This seamless integration enables developers to weave sophisticated crypto analytics into conversational AI workflows, enhancing the intelligence and responsiveness of their assistants.