Footprint Analytics

Web3’s AAA Growth Solution: Analyze, Act, Achieve!
Building @hey_maybe_ai & @OmniMCP

[Footprint Analytics @Footprint_Data]

Massive congrats to @ads3_ai ! 🚀
Thrilled to see an industry leader like @animocabrands join the journey to redefine Web3 advertising. Well deserved!

[Ads3 @ads3_ai]

📢https://t.co/pcFKbsSvE0 Secures Strategic Investment from Animoca Brands @animocabrands to Redefine Web3 Ads

🔥https://t.co/pcFKbsSvE0, 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 https://t.co/pcFKbsSvE0’s global expansion strategy and further the development of its decentralized advertising technology stack.

This latest investment builds upon https://t.co/pcFKbsSvE0'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 https://t.co/pcFKbsSvE0's vision to bridge the Web2 and Web3 economies.🏆

https://t.co/pcFKbsSvE0 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, https://t.co/pcFKbsSvE0 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.

[Footprint Analytics @Footprint_Data]

@ads3_ai 🤝 100%

[Footprint Analytics @Footprint_Data]

Great to see the momentum behind the Ads3 ecosystem! Now spanning 200+ Web3 projects across exchanges, networks, infra, AI, gaming, and more.

Smarter advertising and measurable growth are becoming essential for teams looking to scale.

Worth keeping an eye on their progress @ads3_ai

[Ads3 @ads3_ai]

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 → https://t.co/BBD7DdDfgA

[Footprint Analytics @Footprint_Data]

@ads3_ai Strong progress from the Ads3 team! Congrats, team!

[Footprint Analytics @Footprint_Data]

@vern33 @Dune 😆

[Animoca Brands Research @animocaresearch]

2025 Q3 Listing Report

1️⃣Q3 Altcoin Listings: In the third quarter, altcoin exchange listing activities transitioned from a prolonged low phase into a more unpredictable, model—reflecting broader market swings and uncertainty that we expect to persist. 📉➡️📈

2️⃣ July's Initial Recovery: The first signs of rebound emerged in July, spearheaded by aggressive listing pushes from @bitget and @MEXC_Official 🚀

3️⃣ September Delivers Full Rebound: By September, activity exploded with robust listings from both major and mid-tier exchanges💥

4️⃣ Beyond Alts: Tokenized Stocks Gain Traction: Exchanges are diversifying aggressively with tokenized stocks and innovative programs;

5️⃣ Alpha Programs Sweep the Field: 7 out of 10 exchanges in our report now feature some Alpha initiative; six, including @binance , focus on curating high-potential tokens for easy direct trading, while @okx innovates with wallet-centric incentives to amplify volume on select DEX-listed gems. 🌟

Read here: https://t.co/CMyNxcZmVX

[Footprint Analytics @Footprint_Data]

Many teams want automation, but struggle to turn real processes into systems that evolve with changing roles and data.

MaybeAI is now adding consulting support on top of the platform, helping teams design, define, and deliver automation that works.

For teams exploring this path, it’s worth a look:

[MaybeAI @hey_maybe_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:
https://t.co/CGGhizqZcp

[Yat Siu @ysiu]

Discussing our public plans with NASDAQ:CURR on @YahooFinance Market Sunrise and the potential and growth of the token ecosystem powered by @animocabrands and some of our investors including @SoftBank https://t.co/m60JTUsiqS

[Footprint Analytics @Footprint_Data]

More details below:
https://t.co/qw92X8aQ86

[Footprint Analytics @Footprint_Data]

Web3 community management, without the manual grind.

MaybeAI is turning Telegram into a programmable surface, with smart workflows for content rotation, live updates, safety filters, and engagement analytics.

A powerful toolset for teams who run on data.

[MaybeAI @hey_maybe_ai]

Manage and grow your Web3 community, fully automated, fully under your control.

The MaybeAI Digital Marketing Platform turns Telegram operations into intelligent, repeatable workflows.

Here’s what it can do:
1️⃣ Auto topic rotation by timezone
2️⃣ Use your own accounts, no shared bots
3️⃣ Live content from CoinDesk, Twitter, or your website
4️⃣ Safety filters and blacklists to prevent bans
5️⃣ Analytics that show what works

From content planning to engagement analytics, all in one workflow.

Watch the demo:

[Footprint Analytics @Footprint_Data]

From fragmentation to convergence, the exchange landscape is shifting fast.

@animocaresearch’s latest report outlines how CEXs and DEXs are evolving into full-scale crypto super-apps, and what’s holding back the next wave of users.

A timely read 👇

[Animoca Brands Research @animocaresearch]

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 👉 https://t.co/gn4PJtG3fg

[Footprint Analytics @Footprint_Data]

Sept 29–30 (UTC) → Workflow Airdrop🚀

Follow, Sign up, and comment your idea.

@hey_maybe_ai will pick 3 winners and deliver.

[MaybeAI @hey_maybe_ai]

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 https://t.co/tYvtBKcnU6

3️⃣ Comment below with your workflow need

We’ll pick 3 winners → deliver your workflow.

[Footprint Analytics @Footprint_Data]

80+ workflows in one month. Not for show, but to save real hours on community ops, content, recruiting, and more.

@hey_maybe_ai is what automation should feel like:
No code, no drag-and-drop, just describe the task and run.

Built for scale. Built for people who do the work.

[MaybeAI @hey_maybe_ai]

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.

[MaybeAI @hey_maybe_ai]

We’ve been sharing lots of new demo videos lately, and you can now find them all in one place.

Our YouTube channel will keep growing with:
- Workflow automation guides
- Use case demos
- Tips for getting the most out of Maybe AI

Subscribe here 🔗
https://t.co/DsQWCAe71t

[Footprint Analytics @Footprint_Data]

Congrats to @HashGlobal and @yzilabs!

We will co-build the @BNBCHAIN ecosystem with Hash Global, driving Web3 mass adoption.

[Hash Global @HashGlobal]

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: https://t.co/XTIWOtoMXK

[Footprint Analytics @Footprint_Data]

A shifting listings landscape in 1H 2025 & Strong insights from @animocaresearch

- Binance Alpha reshaped DEX liquidity and token strategy
- Mid-size exchanges lost share as meme launchpads surged
- Larger FDV projects dominated volume, but price returns stayed weak

Solid breakdown of market structure in flux.

[Animoca Brands Research @animocaresearch]

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_ , [email protected]
[email protected]

[Footprint Analytics @Footprint_Data]

@hey_maybe_ai Appreciate the words, and the ride.

From building the rails to watching them run, it’s been about one thing: making blockchain data usable, actionable, and trustworthy.

Here’s to what comes next.

[Footprint Analytics @Footprint_Data]

@WattterDjiang We’re just getting started.

[Footprint Analytics @Footprint_Data]

It’s D-day: the anniversary of Footprint Analytics going live.🥂

Grateful for everyone who’s been part of the journey!

[Footprint Analytics @Footprint_Data]

A powerful breakdown of why MCP, despite its transformative potential, hasn’t seen widespread adoption.

Maybe @hey_maybe_ai is tackling the hard part: turning complex agent workflows into something intuitive, stable, and accessible.

Real progress happens when execution becomes effortless.

[MaybeAI @hey_maybe_ai]

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.