The project: MEV research content aggregator and search engine

Contributors: @unlock_VALue, @Freddmannen

Introducing for MEV enjoyers to contribute ( and fetch content ( across research papers, blog, articles, YouTube videos, podcasts, Twitter threads […].

We already have >100 papers, ~150 articles, >1000 curated YouTube videos, 80 referred content websites, ~40 Twitter threads, 29 recommended YouTube channel handles.

What: is an open-source initiative dedicated to gathering and curating research on Maximal Extractable Value (MEV), incentive alignment, mechanism design, and their implications in the blockchain ecosystem, with a specific focus on Ethereum.
We already have contributors to whom we are deeply thankful for joining the journey!

Why: @unlock_VALue originally launched the project since there was no single location for everything MEV, which made onboarding to the ecosystem more challenging. Extremely good content was scattered across many communications channels.

Vision: The current end-game is to provide an MEV research content search engine/chatbot a la NFX Chat to refer to curated content given a natural language MEV research request as input.

Right now we are at the phase of gathering and curating research content in a scalable way, and we will be soon moving to insights extractions, parsing, and fetching (likely the least intuitive in the loop).

We are actively seeking to decentralize that project further, and we are welcoming all suggestions aligned with this goal.

Where can I learn more: Every detail is available in the of the GitHub repository.

What and how to contribute:

  • Research: We are seeking all research content on the topics listed by Flashbots. Do not worry about adding content already referred to in the repo, filtering is taken care of. You can also add your handle to be noted as a referrer should you want to! First contributed first referred :slight_smile:
  • Non-research e.g. development, project management: The project seeks contributors for both research and tooling development to optimize for referencing and fetching content back. For now, research is displayed as a Google Sheet. This is a work in progress.

Please state any feedback you might have here, in particular around Contribution User Experience. You can also create pull requests or open issues in the repository.

Thank you and we are looking forward to your contributions! :saluting_face:

High frequency word-spreaders to whom we are thankful:
Reid Yager, 0xTaker, George Zhang, There.Is.No.Alignment, casslin.eth, 0xstrider_, etheraael, Wasif Iqbal, JChen, and counting :face_holding_back_tears:

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