MCP Order Flow Server

@fintools-ai

リポジトリ

基本情報

カテゴリ

その他

トランスポート

stdio

作者

fintools-ai

MCP Order Flow Server について

This is the mcp to fetch and get order flow information

#mcp-order-flow#order-flow-analysis#options-trading

MCP Order Flow Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "mcp-order-flow-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP Order Flow Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP Order Flow Server?

MCP Order Flow Server provides real-time order flow analysis for options trading decisions. It consumes quote data from Redis and delivers structured analysis through MCP tools, including momentum indicators, size dynamics, pattern detection, support/resistance levels, and market behavior flags.

How to use MCP Order Flow Server?

Install dependencies, configure Redis environment variables (REDIS_HOST, REDIS_PORT, etc.), and run the server via python -m src.mcp_server or the dev_start.sh script. The primary tool is analyze_order_flow(ticker, history, include_patterns), which returns XML-formatted order flow data.

Key features of MCP Order Flow Server

Real-time momentum indicators (bid/ask lifts, drops, price changes)
Size dynamics analysis (volume patterns, large order detection)
Pattern detection (absorption, stacking, sweeps, momentum shifts)
Support/resistance level identification from order flow
Market behavior flags (YES/NO) for LLM interpretation
Background processing every 1 second for updated metrics

Use cases of MCP Order Flow Server

Enabling LLM agents to make informed options trading decisions
Detecting institutional accumulation or distribution via absorption patterns
Identifying trend initiation or reversal through momentum shifts
Recognizing aggressive execution or stop hunting with sweep detection
Providing structured order flow context for automated trading assistants

よくある質問

What are the runtime dependencies?

Python 3.10 or later, a running Redis server, and the `mcp-trading-data-broker` publishing quotes into Redis.

How is the data stored and for how long?

Raw quotes and detected patterns are stored in Redis with a default TTL of 3600 seconds. Calculated metrics have TTLs ranging from 60 to 600 seconds depending on the window.

What patterns does the server detect?

It detects absorption, stacking, momentum shifts, and sweeps. Each pattern has specific trigger conditions defined in the README (e.g., >15k size change for sweeps).

How do I configure the server?

Set environment variables such as `REDIS_HOST`, `REDIS_PORT`, `REDIS_DB`, `LOG_LEVEL`, and `PROCESSOR_INTERVAL` (default 1 second). A Claude Desktop configuration example is provided for integration.

Is authentication or authorization supported?

The README does not mention any authentication or authorization mechanisms for the MCP server or its Redis connection. An optional `REDIS_PASSWORD` environment variable exists for Redis authentication.

「その他」の他のコンテンツ

Maestro

mobile-dev-inc

Painless E2E Automation for Mobile and Web

14.8K

MCP Toolbox for Databases

googleapis

MCP Toolbox for Databases is an open source MCP server for databases.

15.9K

The Living Bread

A free remote MCP server for The Living Bread. Bible passages read word for word from a stored public domain text with an evidence label, keyword search and cross references, real churches, gatherings and prayer groups w