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MCP Server for Screener.in

@minhaj3

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

minhaj3

MCP Server for Screener.in について

概要はまだありません

MCP Server for Screener.in の設定

標準の設定はありません

このサーバーの README には解析可能な MCP 設定ブロックが含まれていません。インストール手順はリポジトリをご確認ください。

リポジトリ

MCP Server for Screener.in 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 Server for Screener.in?

The MCP Server for Screener.in is an open-source server that fetches financial data from screener.in and calculates the Market Capitalization to Profit (MCP) ratio for listed companies. It is designed for developers, analysts, and financial enthusiasts who need customizable financial data analysis and technical trading tools.

How to use MCP Server for Screener.in?

Clone the repository, set up a Python virtual environment, install dependencies, and create a .env file with your screener.in CSRF token, session ID, and middleware token. Run the server using mcp dev server.py and access it at http://localhost:6274. Use the GET /mcp endpoint with a symbol parameter (e.g., ?symbol=RELIANCE) to fetch the MCP ratio and market cap/profit data.

Features of MCP Server for Screener.in

  • Fetches financial data from screener.in.
  • Calculates the Market Capitalization to Profit (MCP) ratio.
  • Provides Moving Average (MA) analysis and signals.
  • Computes Relative Strength Index (RSI).
  • Generates actionable trade recommendations.
  • Creates swing trading and intraday strategy prompts.
  • Supports ticker analysis and comparison.

Use cases of MCP Server for Screener.in

  • Evaluate a company's valuation relative to its profitability.
  • Generate buy/sell signals using MA and RSI.
  • Build custom swing trading or intraday strategies.
  • Compare multiple stocks to identify the best trading opportunity.

よくある質問

1

What is the MCP ratio?

The MCP (Market Capitalization to Profit) ratio is a metric that evaluates a company's valuation relative to its profitability, calculated as market capitalization divided by profit.

2

What are the runtime requirements?

Python 3.8+, MCP Inspector CLI tool, and a screener.in middleware token (CSRF token, session ID, and middleware token stored in a `.env` file).

3

How can I customize the server?

You can modify the logic in `mcp_calculator.py` to add additional metrics or customize the MCP calculation.

4

What transport does the server use?

The server runs as an HTTP server on localhost (default port 6274) and is tested with the MCP Inspector.

5

Is the server free to use?

Yes, the project is open-source under the MIT License.

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