Mattbusel/Reddit-Options-Trader-ROT-
by Various
A modular research pipeline that turns trending Reddit discussions into structured market events and options trade ideas.
MCP
Mattbusel/Reddit-Options-Trader-ROT-
Added 1 June 2026
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_pageROT_REDDIT_CLIENT_IDROT_REDDIT_CLIENT_SECRETROT_REDDIT_USER_AGENTROT_REDDIT_SUBREDDITSROT_REDDIT_LISTINGROT_REDDIT_LIMIT_PER_SUBROT_REDDIT_POLL_INTERVAL_SROT_LLM_PROVIDERROT_LLM_API_KEYROT_LLM_MODELROT_LLM_MAX_TOKENSROT_LLM_TEMPERATUREROT_RSS_ENABLEDROT_MARKET_MIN_MARKET_CAPROT_MARKET_CACHE_TTL_SROT_TREND_WINDOW_SROT_TREND_THRESHOLDROT_ALERT_DISCORD_WEBHOOK_URLROT_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.
Get the free Developer’s Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.