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Mattbusel/Reddit-Options-Trader-ROT-

by Various

A modular research pipeline that turns trending Reddit discussions into structured market events and options trade ideas.

M

MCP

Mattbusel/Reddit-Options-Trader-ROT-

Added 1 June 2026

#finance #nlp #options-trading #python #reddit #signals

Overview

A modular research pipeline in Python that processes trending Reddit discussions, extracts structured market events, and generates options trade ideas. It allows developers to plug in data sources and analysis modules to create custom trading signals.

Best for

Best for
Developers exploring sentiment-driven options trading with Python

Use cases

  • Monitor Reddit communities for stock and options sentiment shifts
  • Generate structured trade ideas from unstructured discussion threads
  • Build and backtest custom strategies using the modular pipeline

How to use

Install

pip install -e ".[dev]"

Tools exposed

  • render_positions_page
  • ROT_REDDIT_CLIENT_ID
  • ROT_REDDIT_CLIENT_SECRET
  • ROT_REDDIT_USER_AGENT
  • ROT_REDDIT_SUBREDDITS
  • ROT_REDDIT_LISTING
  • ROT_REDDIT_LIMIT_PER_SUB
  • ROT_REDDIT_POLL_INTERVAL_S
  • ROT_LLM_PROVIDER
  • ROT_LLM_API_KEY
  • ROT_LLM_MODEL
  • ROT_LLM_MAX_TOKENS
  • ROT_LLM_TEMPERATURE
  • ROT_RSS_ENABLED
  • ROT_MARKET_MIN_MARKET_CAP
  • ROT_MARKET_CACHE_TTL_S
  • ROT_TREND_WINDOW_S
  • ROT_TREND_THRESHOLD
  • ROT_ALERT_DISCORD_WEBHOOK_URL
  • ROT_STORAGE_ROOT

Tested with

ChatGPT

Notes

A modular research pipeline in Python that processes trending Reddit discussions, extracts structured market events, and generates options trade ideas. It allows developers to plug in data sources and analysis modules to create custom trading signals.

10 stars on GitHub. Last updated 2026-04-27. Licensed MIT.

Use cases

  • Monitor Reddit communities for stock and options sentiment shifts
  • Generate structured trade ideas from unstructured discussion threads
  • Build and backtest custom strategies using the modular pipeline

Pros

  • Modular architecture makes it easy to extend or replace components
  • Python-based, fitting into standard data science workflows
  • Open source with clear input/output points for integration

Cons

  • Small community (10 stars) may mean limited support and updates
  • Requires significant customization to produce actionable trades
  • No built-in backtesting or risk management tools

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Modular architecture makes it easy to extend or replace components
  • Python-based, fitting into standard data science workflows
  • Open source with clear input/output points for integration

Cons

  • Small community (10 stars) may mean limited support and updates
  • Requires significant customization to produce actionable trades
  • No built-in backtesting or risk management tools

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

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