I believe quotes assets have distinct effects on the tokens launched against it. Get all the data here to understand which one is right quote for your asset at launch. Its like finding a match for ur token.

Welcome to Meteora FYI ☄️ The visibility and builder support hub for launchpads building on the Meteora ecosystem. Building around two core pillars: For Visibility - Launchpad Screener: Discover launchpads across the Meteora ecosystem by trading volume, market cap, tokens launched, graduation rates, liquidity, and more. - Quote Screener: Explore tokens with a special focus on custom quote assets and their markets. For Builder Support - Builder Dashboard is a single builder profile that links both your builder history and on-chain traction towards building a reputation in meteora ecosystem.

We are entering an era of information-accruing assets. We're seeing different approaches to this: @supertake uses AI agents to translate natural-language investment takes into managed stock portfolios. @peopledotfun / @cleopetrafun were exploring thesis indexes of prediction markets. @PerpsPadfun backed the indexes by perps. But I believe the real challenge in this category is building the intelligence capable of translating an abstract thesis into an accurately constructed portfolio of market positions. A single thesis can imply dozens of outcomes across completely different markets. - Which outcomes actually support the thesis? - Which markets offer the best exposure to those outcomes? - How should capital be allocated across them? - And how should those positions change as new information emerges? These aren't simple questions that can be solved by matching keywords or asking an LLM to pick a few positions. The entire mechanism is only as good as the intelligence deciding where the capital goes. A poorly constructed portfolio can lose money even when the underlying thesis is correct. You need to understand the information behind a thesis well enough to construct a portfolio that accurately rexpress it through the right positions, at the right prices, with the right exposure. This is the wedge of my experiment. We built an OSINT intelligence engine focused on filtering through the noise, connecting fragmented information, identifying relevant signals, and translating broad speculation into evidence-backed positions. It consistently translates complex, evolving information into positions that extract more value from the information those assets represent. It's a race to turn information into alpha.

Meteora-FYI is now shows token-2022 transfer fees show on both base and quote tokens, right next to the token. To upgrade your own screeners, bump to meteora-ag/[email protected]

Calling all projects recently submitted to the Meteora Hackathon tracks in Crypto Worlds Fair or Stocklana Meteora FYI weighs in both your builder history and on-chain traction towards consideration for amplification, activations & other support.

Compounding MEME/STOCK pair fees into a destination STOCK/USDC LP is kinda smart product overlay to can help bootstrap depth for tokenized stocks. Liquidity of stock normally gets fragmented across many thin, volume-dependent pools and never compounds into deep, usable depth that DeFi (lending, perps, routing, aggregators) can actually build on. Specially due to lots of launchpads promoting multi-pairs which hurts pool depth directly. Concentrated bubble liquidity could be a clever workaround to having multipairs being beneficial to the stock for once My solution to it was a multi-asset pool which is not plausible with the current infra so this seems the best solution for the current markets.