📢Ads3.ai Secures Strategic Investment from Animoca Brands @animocabrands to Redefine Web3 Ads 🔥Ads3.ai, a leading Web3 intelligent advertising platform, announced today the completion of a new strategic funding round with investment from Animoca Brands. This capital injection will support Ads3.ai’s global expansion strategy and further the development of its decentralized advertising technology stack. This latest investment builds upon Ads3.ai's previous funding rounds, having already secured backing from prominent industry institutions, including Web3 Labs, AB Foundation, and Footprint Analytics. The continued support from top-tier investors underscores the market's confidence in Ads3.ai's vision to bridge the Web2 and Web3 economies.🏆 Ads3.ai leverages artificial intelligence to integrate on-chain and off-chain data, providing advertisers with precise user profiling and automated targeting capabilities. A key component of its growth strategy is its exclusive partnerships with leading smartphone manufacturers. By integrating into the native advertising networks of mobile devices, Ads3.ai provides unparalleled access to digital consumers in key emerging markets, including Western Europe, Southeast Asia, and the Middle East. This infrastructure enables the seamless onboarding of Web2 users into the Web3 ecosystem, maximizing ROI for advertisers through data-driven, performance-based pricing models such as OCPC and OCPM.

Over 200 Web3 projects are already part of the Ads3 ecosystem across multiple fronts, covering Exchanges, Networks, Infra, AI, DePIN, Gaming, Memes, and RWA 💙 What drives all these collaborations? Smarter ads, better growth, real users. Who’s the next project to scale with us? 🚀 Explore → ads3.ai

We just published a new piece on the next step for MaybeAI. Many teams know they need automation. The challenge is turning real processes into a system that keeps working as roles, data, and conditions change. This is why we are adding an automation consulting layer on top of the platform. The article covers: • What teams struggle with in practice • Why definition and design matter • How MaybeAI supports end-to-end delivery • What remains the same for individual users Read it here: maybe.ai/blog/why-were-addin…

CEX vs DEX is yesterday’s fight. The real question: Who will become the universal exchange for crypto, where trading, wallets, custody, and apps converge ? Our new report maps the future of exchanges as they morph into full-scale super-apps. We explores: • Why user growth has stalled • The barriers for Web2 adoption • CEX & DEX convergence • The rise of Universal Exchanges Read here 👉 research.animocabrands.com/p…

Workflow Airdrop (Sept 29–30, UTC) We’ll build custom workflows for free! How to join: 1️⃣ Follow @hey_maybe_ai 2️⃣ Sign up on maybe.ai 3️⃣ Comment below with your workflow need We’ll pick 3 winners → deliver your workflow.

80 Workflows That Saved Us Hundreds of Hours We built more than 80 workflows in Maybe AI over the past month. Not to show off, but because we were drowning in repetitive work. Telegram groups need daily messages to stay active. Twitter needs trending content moved and reformatted. Resumes pile up. Bulk emails still involve copy and paste. 1. Workflows that saved hundreds of hours Community automation - Scheduled posts by a Telegram digital host for group activity (already helped 10 group owners free their hands) - Automatic group-chat summaries (24 hours of content in 3 minutes) - Community sentiment analysis (finds investment opportunities 72 hours faster than manual work) Social automation - Tweet style analysis plus auto-replies (mimic any account’s tone) - Hot content rewriting end to end (EN→ZH with image generation) - LinkedIn autoposting (daily news summaries on autopilot) Recruiting and marketing automation - Resume key-info extraction (outputs structured tables from Google Drive) - Personalized bulk email (Apollo data plus tailored copy) 2. These are real productivity tools A friend used the Telegram activity workflow and grew their group by 40% in three months. Another used the tweet analysis workflow and found two 10x coins. We use the recruiting workflow to screen resumes and cut 80% of the time. Every workflow can be reused. Swap in your group ID, account, or sheet link and run.

Excited to have the support of @yzilabs for our First Compliant BNB Yield Fund — bridging TradFi capital with the fast-growing BNB ecosystem. We see BNB’s role in Web3 as pivotal, much like Nvidia’s in semiconductors. With partners like @KGIAsia, we’re making secure, liquid, yield-driven products accessible to more investors. 🤝 👉 Learn more: secondary.hashglobal.io/hg-y…

2025 1H Listing Report 1️⃣Binance Alpha, @binance launched in 1H 2025, evolved from wallet-only to a 2.0 version integrating Binance liquidity into DEX trading, followed by Alpha points incentives. 2️⃣Alpha prioritized tokens with FDV under $100M, outperforming other exchanges in price and volume, including Binance’s own listings. 3️⃣Alpha’s rise reduced mid-size exchange listings and cut Binance’s large FDV token 30-day volume by 20%, while @Official_Upbit , @okx , and @Bybit_Official grew. 4️⃣@pumpdotfun meme launchpad generated 10,000 daily tokens and $1-2B DEX volume in Q2, rivaling mid-size exchanges; @HyperliquidX spot volume was <$0.5B but showed growing token activity. 5️⃣Listings lagged despite a bullish-to-bearish market sentiment shift recovering in April; mid-size exchanges saw modest listing increases in May/June. 6️⃣@Binance and @Official_Upbit entered the $100-500M FDV tier (10% of listings); larger FDV projects had balanced multi-exchange listings. 7️⃣Price performance remained negative (day 1 to 30), with no altcoin season; larger FDV token volumes rose, smaller ones shrank, showing market focus on bigger projects. Exchanges include: @binance @Official_Upbit @okx @Bybit_Official @coinbase @bitgetglobal @BithumbOfficial @kucoincom @Gate @MEXC_Official Author 📍 @shuang_log2pi ,@hoidya_ , mingr@animocabrands.com verlebiec@animocabrands.com

MCP Works Great. So Why Isn't Everyone Using It? The Model Context Protocol (MCP) represents AI's biggest breakthrough and accessibility failure. After integrating MCP extensively at Maybe, we've witnessed both its transformative power and why this game-changing technology remains largely unused. The gap isn't philosophical—it's brutally practical. The MCP Breakthrough: When AI Finally Acts MCP solves AI's fundamental limitation: the inability to execute. Traditional AI ends with suggestions requiring human translation into action. MCP eliminates this bottleneck entirely. Consider location planning: Instead of suggesting "find a place halfway between you two," MCP-enabled systems calculate precise coordinates, identify the geographic midpoint, query mapping services for venues within specified parameters, filter by criteria like parking availability, and deliver actionable recommendations. The entire workflow executes autonomously. For research automation, the difference is even more dramatic. Traditional AI might summarize a paper. With MCP, the system processes the document, generates chapter analysis, creates a navigable website, converts text to speech, and delivers a complete multimedia research companion—all from a single natural language request. This isn't incremental improvement; it's categorical transformation from AI advisor to AI executor. The Brutal Reality: Why MCP Adoption Remains Minimal Despite MCP's potential, actual adoption remains frustratingly low. The barriers aren't minor inconveniences—they're fundamental blockers. - Technical Complexity That Excludes 95% of Users: MCP requires specialized IDE environments, server configurations, and integration expertise that eliminates non-technical users. The installation process alone involves multiple dependencies, environment variables, and troubleshooting steps that challenge experienced developers. - Execution Inconsistency That Breaks Business Use: MCP-powered agents can choose different tool sequences for identical tasks. This non-determinism makes MCP unsuitable for scenarios requiring reliable, repeatable outcomes—which describes most business applications. Unreliable automation is often worse than no automation. - Ecosystem Fragility That Threatens Long-term Viability: The most innovative MCPs come from individual developers. When underlying APIs change, these integrations break. Maintenance is inconsistent, documentation becomes outdated, and critical functionality disappears without warning. - Platform Lock-in That Limits Flexibility: MCP requires specific clients like Cursor or specialized development environments, creating dependency chains that force architectural decisions many organizations aren't prepared to make. The Staggering Potential Being Wasted These barriers prevent access to genuinely transformative capabilities: - Multi-Platform Workflow Orchestration: Coordinating actions across different services and APIs in ways that would require months of custom development - Context-Aware Automation: AI systems that adapt tool selection based on real-time conditions and user history - Natural Language Programming: Describing complex processes conversationally and watching them execute reliably - Autonomous Problem-Solving: AI agents that break down requests into subtasks, execute across multiple systems, and handle error recovery automatically The gap between this potential and current accessibility represents one of AI's largest missed opportunities. The Democratization Imperative At Maybe, we see MCP's barriers as design challenges demanding solutions. Technical complexity doesn't have to equal user complexity. The most successful platforms hide sophisticated capabilities behind effortless experiences. - Invisible Infrastructure: Handle server setup, dependency management, and environment configuration automatically, so users focus on outcomes rather than operations. - Intelligent Orchestration: Build systems smart enough to choose optimal execution paths and recover from failures without user intervention. - Progressive Disclosure: Start with simple interfaces for common use cases, revealing advanced capabilities as users' needs evolve. - Ecosystem Resilience: Create abstraction layers that adapt to API changes automatically, protecting user workflows from underlying instability. The Path Forward: Making Power Accessible The future belongs to platforms that solve MCP's accessibility problem without sacrificing capabilities. This requires radical simplification—reducing MCP workflow creation to natural language descriptions that generate reliable execution automatically—plus infrastructure abstraction that handles all technical complexity invisibly. The companies that succeed in making MCP's power accessible will define how humans interact with autonomous AI systems. The opportunity is enormous precisely because the barriers are high. When those barriers fall, the market expands from thousands of technical users to millions who want to accomplish more with less effort. The question isn't whether MCP's capabilities will become universally accessible—it's how quickly we can make that happen. The technology exists. The demand exists. What's missing is the platform layer that makes sophisticated AI capabilities feel effortless to use. MCP proves that AI can bridge human intention with real-world execution. Now we need to bridge MCP's potential with human accessibility. The technology that makes AI truly useful shouldn't require users to become technologists.

Now live on Maybe: Try Kimi and more LLMs — seamlessly switch and experiment with multiple models in one place. 😍

Congrats on the major upgrade! 🎉 Love seeing @KOL_AI_Official leverage Maybe's capabilities to build something truly specialized - an Intelligent Content Creation Platform where AI completely handles social media content generation and automated operations. This showcases the power of accessible AI: creators can now effortlessly build their personal brand and influence without getting bogged down in technical complexity. This is the future we're working toward: AI that truly understands and serves human creativity. 🚀

The future isn't about "what if"—it's about "what's possible." 🚀 Today, we're evolving from OmniMCP to Maybe (maybe.ai) Maybe you need a personal assistant. Maybe you want to solve complex problems. Maybe you have ideas worth sharing. At Maybe, every "maybe" becomes reality. ✨ Our vision has grown far beyond MCP connections. We're building a platform where AI agents become your tools, your partners, even your business. And yes—OmniMCP lives on as a powerful tool within the Maybe ecosystem, connecting your agents to unlimited possibilities. Ready to turn your maybes into reality?

🎉 Beosin is thrilled to release the 2025 H1 Global Web3 Security Report! 🤝 Great thanks to Blockchain Security Alliance Member @Footprint_Data for contributing to the report! 🧵 Dive into the report to see the insights into Web3 security landscape.