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MCP Market Data Server

@fintools-ai

关于 MCP Market Data Server

Standalone server designed to deliver market data insights to AI trading agents. It processes data from external brokers and computes structured information to help LLMs and other AI systems make more informed trading decisions using JSON RPC protocol

基本信息

分类

金融与商务

运行时

python

传输方式

stdio

发布者

fintools-ai

配置

暂无标准配置

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代码仓库

工具

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概览

What is MCP Market Data Server?

MCP Market Data Server provides financial market data analysis tools for LLM agents and trading applications. It implements the Model Context Protocol (MCP) and integrates with the Twelve Data API to offer institutional-grade analysis like volume profile, technical indicators, zones, and ORB.

How to use MCP Market Data Server?

Use an MCP client to call the server’s tools with a stock symbol. The server provides four tools: financial_volume_profile, financial_technical_analysis, financial_technical_zones, and analyze_open_interest.

Key features of MCP Market Data Server

  • Volume Profile Analysis with POC and value area
  • 15+ technical indicators across multiple timeframes
  • Smart Zone Analysis using Fibonacci, ATR, and volume
  • Opening Range Breakout (ORB) with multi-period analysis
  • Async/await architecture for high performance
  • Secure API key management and comprehensive logging

Use cases of MCP Market Data Server

  • Scalping: Find 1-minute support levels for rapid trades
  • Swing Trading: Identify 5-minute resistance zones for breakout entries
  • Position Trading: Analyze daily technical trends for portfolio direction
  • 0DTE Options: Use ORB analysis for intraday breakout confirmation
  • Combined analysis: Get volume profile, indicators, and zones in one query

FAQ from MCP Market Data Server

What API does the server use for market data?

It uses the Twelve Data API.

What runtime is required?

Python 3.8 or higher and the FastMCP library.

What tools are available?

Four tools: financial_volume_profile, financial_technical_analysis, financial_technical_zones, and analyze_open_interest.

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