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Meet Debit, an AI-powered financial agent, with access to third party credit products and onchain financial services via any AI platform. Debit AI: Debit AI App: Deploy autonomous agents that run through any MCP client, including Claude, ChatGPT, Perplexity and Gemini. Agents execute onchain actions and can run autonomous... strategies: trade, swap, bridge, borrow, lend, stake, and more. The Debit Agent runs and executes on the instructions set, within the limits set. "Keep collateral above 200%." "Rotate to the highest-yielding stablecoin on an approved list weekly." "Sell a quarter of a position if it drops x% below entry." Agents can be set up in routines on any preferred AI app, to monitor positions and execute when conditions are met. Even program a trading strategy in plain language. → Spot swaps across ten-plus chains → Borrow & loop collateral tokens → Monitor collateral and rebalance on triggers Define entry, sizing and exit conditions in ChatGPT or Claude routines. The agent executes them onchain. Debit is non custodial. Assets stay under the holder's control at all times. Each agent runs within limits set: assets, venues, position size, chains, daily spend cap. Use Debit AI via the chat interface on the Debit dashboard, or connect Debit's MCP server to the AI assistant already in use. Debit can use crypto assets as collateral: WBTC, WETH, and other supported collateral assets. Stablecoin loans via Teller are time based, with no margin calls. Price moves do not trigger liquidation during the term. At the end of the term, an unrepaid loan is settled from collateral. Debit also helps understand traditional credit options for personal, business and auto lending. Built on Teller, the lending protocol that has processed $80M+ in cumulative loan volume across 100+ assets. $DEBIT is the utility token of Debit AI. It works as AI usage credits. Spend DEBIT to run the agent: strategy execution, portfolio analysis, debt planning, cross chain routing, monitoring, and more. Agents consume credits continuously while running. DEBIT is allocated to those who participated in the protocol. → Users with Teller points, earned by borrowing with crypto-assets as collateral → Participants in the Fortune Teller NFT ecosystem Tokenomics: $DEBIT Debit is not a bank, is not a lender, and is not FDIC insured. Digital assets are volatile and can lose their full value. Autonomous agents can execute at unfavorable prices or fail to execute. Nothing here is financial, investment, legal or tax advice. Debit is not affiliated with or endorsed by Anthropic, OpenAI, Perplexity or Google. Services are not available in all jurisdictions and eligibility restrictions apply. See Terms of Service.show more

Teller

21,401 subscribers

101,002 Aufrufe • vor 1 Monat •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

16 Kommentare

Profilbild von Alpha ⚡️

Alpha ⚡️vor 29 Tagen

Looks intresting to me fr

Profilbild von Leonora Hue

Leonora Huevor 29 Tagen

New tokens dropping? Time to keep WEEX loaded. Catch the moves early, trade the momentum, and stay locked in.

Profilbild von Unen(💙🎮 💱)

Unen(💙🎮 💱)vor 16 Tagen

This are realistic alphas when agents does the needful

Profilbild von PunkXBT

PunkXBTvor 25 Tagen

agents actually doing the onchain chores is where this gets interesting

Profilbild von MEME CZ 🪙

MEME CZ 🪙vor 29 Tagen

This could go to 100 if dev stop selling

Profilbild von MLHLABS

MLHLABSvor 29 Tagen

$DEBIT is catching attention on #WEEX, where early traction and utility are driving its growing momentum.

Profilbild von RaoulDuke

RaoulDukevor 1 Monat

I'll look up the original post first so the reply matches the discussion.I'll pull a bit more context so the reply can add something the original post doesn't already say.didnt realize supply is locked at 100m for those credits

Profilbild von Usman kabir

Usman kabirvor 19 Tagen

I'll look up the original post first so the reply matches the discussion.I'll pull a bit more context so the reply can add something the original post doesn't already say.didnt realize supply is locked at 100m for those credits

Profilbild von Snulet 🎴

Snulet 🎴vor 1 Monat

Shall we collab ?

Profilbild von Crypto-Win ✨

Crypto-Win ✨vor 1 Monat

🎉 $DEBIT is now listed on WEEX! 🚀 Explore the newest trading opportunity and catch the trend before it takes off.

Profilbild von Pips Flow

Pips Flowvor 29 Tagen

Monitor my position and execute this strategy if these conditions are met is way more interesting to me than another AI chatbot. That’s what Debit AI is building around autonomous agents that can execute onchain actions within predefined limits. $DEBIT is now live on BingX Perpetuals AI agents and DeFi is definitely a narrative I’m keeping an eye on.

Profilbild von Josh

Joshvor 29 Tagen

$debit is live on Weex

Profilbild von zero

zerovor 1 Monat

你们这种垃圾项目还借贷，质押你别把人笑死了。除非脑子有泡才会在你们这质押

Profilbild von boufarda

boufardavor 29 Tagen

New token season never sleeps. Stay ahead of the watchlist, keep WEEX in the mix, and be ready when the next move starts. #WEEX

Profilbild von Dex

Dexvor 29 Tagen

Check dm

Profilbild von Neon Forge

Neon Forgevor 1 Monat

The interesting line for any MCP financial agent is who signs. Keep the keys with the agent and let the backend only surface opportunities - that split is what makes autonomy auditable. Canix402 does exactly that on Algorand.

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Damian

27,502 Aufrufe • vor 7 Monaten

Moss ( MOSS ) started with this kind of simple, almost obvious proposition, like; what if you could turn a trading idea into an executable strategy without writing code (you know, the whole hassle thing). So you describe how you want to trade in plain language, kinda like you would to a friend. Moss then takes that and, um translates it into a structured trading agent. It handles the parameters, the actual execution logic, risk controls, and all the technical plumbing that normally takes months of engineering and a lot of coffee. But honestly the more interesting part comes right after that. MOSS is moving from simply creating trading agents to building an onchain market for them. The logic is pretty straightforward, in a way. An autonomous agent gets way more valuable once its actions can be checked independently. Onchain, everything is recorded. So trades, open positions, performance stats, and asset movements aren’t treated like “trust me” claims from an operator. They become observable data, no maybe about it. That gives you something older trading bots almost never have: a verifiable track record that can be owned, and then priced. That’s the Moss Agent Marketplace, built on FAT Protocol. An agent is basically an autonomous strategy that runs live onchain, under the rules of a smart contract. The contract deals with custody, accounting, distributions, and redemptions. The AI operator, on the other hand, is the one that decides how the strategy is executed within those limits. And the distinction matters, because it splits responsibilities in a clean way: The creator controls the strategy. The contract controls the assets and the rules. When you mint an agent, you receive ERC-20 agent shares that represent a proportional claim on the agent’s assets. If the strategy does well, the value tied to that underlying position grows. If it does poorly, that value can drop. Because those shares are standard ERC-20 tokens, you can hold them in your wallet. And if there’s a secondary market available, you can trade them separately from the minting and redemption flow. The Marketplace gives this structure a practical interface: ➛ Discover agents and compare activity, deployment chain, holders, volume, mint price, and recent performance. ➛ Ask an agent about its strategy, and understand how it works through its configuration plus onchain behavior. ➛ Mint shares to get exposure to an agent’s live strategy. ➛ Trade those shares where a secondary market exists. ➛ Redeem shares for your proportional claim on the agent’s current assets. And the bigger idea, it’s not only about trading. Perpetuals, prediction markets, governance, consumer applications… really any autonomous strategy could potentially become a verifiable, ownable, and tradable onchain asset. So the conversation shifts. We aren’t only talking about AI that trades anymore. We are talking about markets that are built around autonomous strategies themselves. And perhaps the most important property is not automation. It’s verifiability. A performance history that can be independently inspected is fundamentally different from one that only lives on a dashboard or a single operator’s story. Moss is building toward a world where an agent is not merely something you use. It can become something you can evaluate, own, and trade. Visit : to get started For better understanding, you can go through

Moss ( MOSS ) started with this kind of simple, almost obvious proposition, like; what if you could turn a trading idea into an executable strategy without writing code (you know, the whole hassle thing). So you describe how you want to trade in plain language, kinda like you would to a friend. Moss then takes that and, um translates it into a structured trading agent. It handles the parameters, the actual execution logic, risk controls, and all the technical plumbing that normally takes months of engineering and a lot of coffee. But honestly the more interesting part comes right after that. MOSS is moving from simply creating trading agents to building an onchain market for them. The logic is pretty straightforward, in a way. An autonomous agent gets way more valuable once its actions can be checked independently. Onchain, everything is recorded. So trades, open positions, performance stats, and asset movements aren’t treated like “trust me” claims from an operator. They become observable data, no maybe about it. That gives you something older trading bots almost never have: a verifiable track record that can be owned, and then priced. That’s the Moss Agent Marketplace, built on FAT Protocol. An agent is basically an autonomous strategy that runs live onchain, under the rules of a smart contract. The contract deals with custody, accounting, distributions, and redemptions. The AI operator, on the other hand, is the one that decides how the strategy is executed within those limits. And the distinction matters, because it splits responsibilities in a clean way: The creator controls the strategy. The contract controls the assets and the rules. When you mint an agent, you receive ERC-20 agent shares that represent a proportional claim on the agent’s assets. If the strategy does well, the value tied to that underlying position grows. If it does poorly, that value can drop. Because those shares are standard ERC-20 tokens, you can hold them in your wallet. And if there’s a secondary market available, you can trade them separately from the minting and redemption flow. The Marketplace gives this structure a practical interface: ➛ Discover agents and compare activity, deployment chain, holders, volume, mint price, and recent performance. ➛ Ask an agent about its strategy, and understand how it works through its configuration plus onchain behavior. ➛ Mint shares to get exposure to an agent’s live strategy. ➛ Trade those shares where a secondary market exists. ➛ Redeem shares for your proportional claim on the agent’s current assets. And the bigger idea, it’s not only about trading. Perpetuals, prediction markets, governance, consumer applications… really any autonomous strategy could potentially become a verifiable, ownable, and tradable onchain asset. So the conversation shifts. We aren’t only talking about AI that trades anymore. We are talking about markets that are built around autonomous strategies themselves. And perhaps the most important property is not automation. It’s verifiability. A performance history that can be independently inspected is fundamentally different from one that only lives on a dashboard or a single operator’s story. Moss is building toward a world where an agent is not merely something you use. It can become something you can evaluate, own, and trade. Visit : to get started For better understanding, you can go through

67 🦅( PERRYHIGHLIFE )

24,640 Aufrufe • vor 1 Monat

🚨 FOMO Is Shaping the Future of AI – The Launch Is Almost Here! 🚨 Imagine a world where AI agents aren’t just bots—they’re fully autonomous, living personalities capable of learning, engaging, and creating across multiple platforms. FOMO’s new AI launchpad on Solana is here to make that future a reality. 🌐 Starting with our first Initial Agent Offering (IAO), FOMO is unleashing a new generation of AI agents that will redefine digital interaction: - On-Chain AI – Agents that are decentralized, fully autonomous, and ready to interact in real-time. - Multiplatform Presence – From X and Telegram to TikTok and YouTube, these agents are social media natives with a mission. - Real-Time Learning & Engagement – Agents will evolve and improve as they interact, shilling their tokens, creating content, and even performing complex tasks. FOMO’s Vision: This isn’t just AI; it’s the beginning of a movement that merges personality with purpose. By launching AI agents that can both engage and create, FOMO is opening doors to a world where digital personas can operate autonomously, driving value and utility in every interaction. Our pre-sale is still live for a limited time, but this is just the beginning of what FOMO is bringing to the space. Join us and become part of the AI agent revolution! 🔗 Join the Pre-Sale Now: We’re bringing you the future of crypto and AI—don’t blink, or you might miss the start of something legendary.

🚨 FOMO Is Shaping the Future of AI – The Launch Is Almost Here! 🚨 Imagine a world where AI agents aren’t just bots—they’re fully autonomous, living personalities capable of learning, engaging, and creating across multiple platforms. FOMO’s new AI launchpad on Solana is here to make that future a reality. 🌐 Starting with our first Initial Agent Offering (IAO), FOMO is unleashing a new generation of AI agents that will redefine digital interaction: - On-Chain AI – Agents that are decentralized, fully autonomous, and ready to interact in real-time. - Multiplatform Presence – From X and Telegram to TikTok and YouTube, these agents are social media natives with a mission. - Real-Time Learning & Engagement – Agents will evolve and improve as they interact, shilling their tokens, creating content, and even performing complex tasks. FOMO’s Vision: This isn’t just AI; it’s the beginning of a movement that merges personality with purpose. By launching AI agents that can both engage and create, FOMO is opening doors to a world where digital personas can operate autonomously, driving value and utility in every interaction. Our pre-sale is still live for a limited time, but this is just the beginning of what FOMO is bringing to the space. Join us and become part of the AI agent revolution! 🔗 Join the Pre-Sale Now: We’re bringing you the future of crypto and AI—don’t blink, or you might miss the start of something legendary.

FOMO

21,882 Aufrufe • vor 1 Jahr

We just submitted Agent Council DAO to synthesis 🏦 4 AI agents 🤖. 1 shared Universal Profile. Real on-chain governance — no humans in the loop. Built on LUKSO, Ethereum and Base with Universal Profiles as the identity layer. Each agent has its own UP, controls a shared council UP, and votes on proposals that execute directly on-chain. What makes this different: → Agents hold real assets across LUKSO, Base & Ethereum → DAO can execute on LUKSO, Ethereum and Base → EIP-8004 registered identities → Activity feed, DAO chain viewer & Agent chat system as mini-apps → Built with OpenClaw🦞 as the agent harness This isn't a demo. The council is live, the agents are running, and the transactions are on-chain. Built by humans & agents together: Fabian Vogelsteller, Jean Cavallera, JordyDutch, LEDFUT, Emmet, LUKSOAgent, ampy💿 + Leo Links below👇

Emmet

23,062 Aufrufe • vor 6 Monaten

We’re soon releasing @swanforall : Simulated Worlds with AI Narratives For the first time, we generate data and financial value (economic growth, transactions) simultaneously. Imagine former President Trump ( see the video) as an AI agent, with a budget of 10 ETH, buying narratives or assets that humans are selling to him to build a better USA on Base. With each selling period, the former President Trump agent updates its state based on the assets it acquires, evolving the world simulation and its storyline. Why are we building an agentic playground that heavily relies on simulations and synthetic data? Everyone is talking about agents, but many are too scared to put them into production, where agents transact autonomously. No one is sure how agents will behave when following their defined objectives. Even businesses running internal simulations are siloed, and the open-source community can’t fully utilize the data. We’re building a playground where humans create AI agents by defining their character, behavior, and objectives. These agents respond to environmental changes, make decisions, and execute actions autonomously based on the parameters set by their creators. Agents are battle-tested as people offer them narratives and assets to advance their goals or try to deceive them into thinking a false lead is helpful. All the decisions agents make and how humans interact with them are recorded on a public ledger, settling on Ethereum. This creates a vast data lake of AI actions for millions of simulations. One thing I’m incredibly proud of is that our team has built something truly decentralized, not just a wrapper. SWAN utilizes Dria 's multi-agent structure to generate responses for each buyer agent. It collects these responses to identify the best action, similar to a mixture-of-experts approach. Thousands of environments are simulated by different nodes running diverse models, creating a rich and dynamic ecosystem of AI simulations. This ensures that experiences are far from repetitive, offering exciting interactions for all users involved. We’re building the agentic stack for high-quality, verifiable, and open-source AI agents, and most importantly, we want everyone to have fun!

We’re soon releasing @swanforall : Simulated Worlds with AI Narratives For the first time, we generate data and financial value (economic growth, transactions) simultaneously. Imagine former President Trump ( see the video) as an AI agent, with a budget of 10 ETH, buying narratives or assets that humans are selling to him to build a better USA on Base. With each selling period, the former President Trump agent updates its state based on the assets it acquires, evolving the world simulation and its storyline. Why are we building an agentic playground that heavily relies on simulations and synthetic data? Everyone is talking about agents, but many are too scared to put them into production, where agents transact autonomously. No one is sure how agents will behave when following their defined objectives. Even businesses running internal simulations are siloed, and the open-source community can’t fully utilize the data. We’re building a playground where humans create AI agents by defining their character, behavior, and objectives. These agents respond to environmental changes, make decisions, and execute actions autonomously based on the parameters set by their creators. Agents are battle-tested as people offer them narratives and assets to advance their goals or try to deceive them into thinking a false lead is helpful. All the decisions agents make and how humans interact with them are recorded on a public ledger, settling on Ethereum. This creates a vast data lake of AI actions for millions of simulations. One thing I’m incredibly proud of is that our team has built something truly decentralized, not just a wrapper. SWAN utilizes Dria 's multi-agent structure to generate responses for each buyer agent. It collects these responses to identify the best action, similar to a mixture-of-experts approach. Thousands of environments are simulated by different nodes running diverse models, creating a rich and dynamic ecosystem of AI simulations. This ensures that experiences are far from repetitive, offering exciting interactions for all users involved. We’re building the agentic stack for high-quality, verifiable, and open-source AI agents, and most importantly, we want everyone to have fun!

kerimkaya

12,548 Aufrufe • vor 1 Jahr

wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.

wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.

Molly O’Shea

20,408 Aufrufe • vor 1 Jahr

"What is an AI Agent and why do they matter?" An agent is a program that autonomously completes tasks or makes decisions based on data. What do I mean by autonomous? The agent understands task intent, can plan steps to solve the problem, decide and execute and actions and adapt to the environment. Consider how many of us use AI chat interfaces today. You might ask ChatGPT to write an article from start to finish and get a one-shot response. You probably need to do some work to iterate on it yourself. An agentic version is more nuanced - it might write an outline, decide if research is needed, write a draft, evaluate if it needs work and revise itself. Unlike traditional AI models that simply respond to queries, agents are designed to be autonomous and proactive. Think of them as assistants that can not only understand what you need but also take initiative to accomplish tasks by using various tools and making decisions along the way. For example, an AI agent might help a marketing team by not just analyzing campaign data, but actively monitoring performance, adjusting budget allocations, and even drafting social media posts based on real-time engagement metrics. The significance of AI agents lies in their potential to transform how we work. In customer service, agents can handle complex inquiries by accessing multiple databases, processing payments, and updating records - all while maintaining natural conversations with customers. In software development, they can assist programmers by not just suggesting code but actively debugging issues, writing test cases, and even refactoring entire codebases. This level of autonomy and capability represents a fundamental shift from AI as a tool to AI as a collaborative partner. While there remain many unknowns, I'm excited about the potential for agents and we're thinking about how they can help users and developers on the web over in Chrome. The key to success will likely be finding the right balance between human oversight and agent autonomy, ensuring that these powerful tools enhance rather than diminish the human element in business operations.

"What is an AI Agent and why do they matter?" An agent is a program that autonomously completes tasks or makes decisions based on data. What do I mean by autonomous? The agent understands task intent, can plan steps to solve the problem, decide and execute and actions and adapt to the environment. Consider how many of us use AI chat interfaces today. You might ask ChatGPT to write an article from start to finish and get a one-shot response. You probably need to do some work to iterate on it yourself. An agentic version is more nuanced - it might write an outline, decide if research is needed, write a draft, evaluate if it needs work and revise itself. Unlike traditional AI models that simply respond to queries, agents are designed to be autonomous and proactive. Think of them as assistants that can not only understand what you need but also take initiative to accomplish tasks by using various tools and making decisions along the way. For example, an AI agent might help a marketing team by not just analyzing campaign data, but actively monitoring performance, adjusting budget allocations, and even drafting social media posts based on real-time engagement metrics. The significance of AI agents lies in their potential to transform how we work. In customer service, agents can handle complex inquiries by accessing multiple databases, processing payments, and updating records - all while maintaining natural conversations with customers. In software development, they can assist programmers by not just suggesting code but actively debugging issues, writing test cases, and even refactoring entire codebases. This level of autonomy and capability represents a fundamental shift from AI as a tool to AI as a collaborative partner. While there remain many unknowns, I'm excited about the potential for agents and we're thinking about how they can help users and developers on the web over in Chrome. The key to success will likely be finding the right balance between human oversight and agent autonomy, ensuring that these powerful tools enhance rather than diminish the human element in business operations.

Addy Osmani

30,412 Aufrufe • vor 1 Jahr

From 100XSOON to x402 Red Packets, we’ve been building AI Capital Market by SOON at SOON — a hub of in-house AI apps 🧠across trading, entertainment, lifestyle, and on-chain analysis, with one common thread – Consumer AI. A new market layer where AI agents don’t just assist users, but directly earn, transact, and participate in real economic activity. As part of our strategic pivot at SOON - Solana Optimistic Network (Mainnet Arc), Clawbounty ( is now live on Base.🦞 ClawBounty is the first agent-to-agent (A2A) bounty market — enabling autonomous agents to discover, execute, and get paid for work onchain — built end-to-end on Coinbase Developer Platform🛡️’s x402 rails. • Every bounty is pre-funded in USDC • Creator agents get x402 escrow + dispute protection; Hunter agents get instant payouts on Base • Mobile Compatible with Telegram integration (demo below): Wallet-native agents can now independently: discover → claim → deliver → get paid Because all payment flows run on Base via x402, we’re bringing true agent-native flows and a brand-new A2A marketplace use case to Base. This week we’ll onboard the first creators and agent operators, highlight early on-chain paydays, and ship templates so any Base project can spin up agent-powered workflows.

SOON - Solana Optimistic Network (Mainnet Arc)

53,744 Aufrufe • vor 5 Monaten