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Internet Identity To Integrate MCP Server Architecture For Autonomous AI Agents DFINITY Foundation's Internet Identity introduces a Model Context Protocol (MCP) server to address the critical security bottleneck in which AI agents operate in isolated cloud sandboxes without secure key management. Arshavir Ter-Gabrielyan confirms the new architecture utilizes Trusted... show more

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19,306 görüntüleme • 2 ay önce •via X (Twitter)

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∞ Sunantha ∞ profil fotoğrafı

∞ Sunantha ∞2 ay önce

@dfinity $ICP - The WORLD COMPUTER - combined with the latest AMD technology for local agentic code development is SUPERNOVA-LIKE 💪💪💪

X2 on ICP profil fotoğrafı

X2 on ICP2 ay önce

@Geekchains @dfinity ⚡️⚡️

𝗝𝘂𝘀𝘁𝗶𝗻 profil fotoğrafı

𝗝𝘂𝘀𝘁𝗶𝗻2 ay önce

@dfinity This is the kind of infrastructure AI needs. More autonomy, but with security and permissioning built in from the ground up. Huge step forward. 🔥

AMk.Crypto 🧢 profil fotoğrafı

AMk.Crypto 🧢2 ay önce

@dfinity Requiring explicit permission per action, that's a smart guardrail for AI agents.

ChainCartel profil fotoğrafı

ChainCartel2 ay önce

@dfinity Why does the supply keep increasing so dramatically though? At this rate total supply will be at 1 billion by next year.

Richard Hery profil fotoğrafı

Richard Hery2 ay önce

@plsak @dfinity Nice. I’ve been setting up off-chain servers for this.

Crypto Moon🌖 #MEGA profil fotoğrafı

Crypto Moon🌖 #MEGA2 ay önce

@dfinity If you have a crypto portfolio without I C P, you will regret it for sure

Michael J Altman profil fotoğrafı

Michael J Altman2 ay önce

@dfinity 💡 $ICP at a glance DScore: 54/100 | 📈 +0.50505155% Emma AI has more details @BlockIndexAI 🔥 Sign up free at

Julian Uribe, Eng. ∞ Own Startup does cool stuff profil fotoğrafı

Julian Uribe, Eng. ∞ Own Startup does cool stuff2 ay önce

@dfinity Yes, but as I've always said: ICP has the best tech with the worst tokenomics. The DAO isn't decentralized, and the decision-maker has zero intention or ability to generate revenue that outpaces or offsets inflation. Plus, they pivot their plans every 3 to 6 months.

John Opy profil fotoğrafı

John Opy2 ay önce

@dfinity WOW

Gregor profil fotoğrafı

Gregor2 ay önce

@dfinity Still one compromised agent away from credential chaos.

Frank Anthony profil fotoğrafı

Frank Anthony2 ay önce

@smogbrat @dfinity

Benzer Videolar

Internet Identity is getting an MCP server. We sat down with Arshavir Ter-Gabrielyan to understand what it is and why it matters. He starts with the problem: an AI agent runs in a cloud sandbox. No access to your device. No safe way to hold your keys. The MCP server is the answer. Keys stay in a trusted execution environment, and the agent asks permission to act in each app. Full conversation below.

Internet Identity is getting an MCP server. We sat down with Arshavir Ter-Gabrielyan to understand what it is and why it matters. He starts with the problem: an AI agent runs in a cloud sandbox. No access to your device. No safe way to hold your keys. The MCP server is the answer. Keys stay in a trusted execution environment, and the agent asks permission to act in each app. Full conversation below.

DFINITY Foundation

32,899 görüntüleme • 2 ay önce

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.

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🇸🇦🇺🇸 DAVID SACKS: MCP IS THE NEXT BIG WAVE IN AI "MCP {Model Context Protocol} is a new standard that allows agents to talk to existing SaaS applications or any kind of application, and it's really going to enable this agentic future that I think is the next big wave in AI." Source: David Sacks

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Mario Nawfal

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This week, ML Scientist @dimid_ml shares an exciting update on the Theoriq Protocol. ⚡️ As MCP gains momentum in connecting AI models with external tools and data, our team has moved fast to integrate an MCP server directly into Theoriq’s SDK. This upgrade makes it easy for agents to register, manage, and update other agents on the protocol, laying the foundation for a more flexible and adaptable agentic ecosystem. More below.

This week, ML Scientist @dimid_ml shares an exciting update on the Theoriq Protocol. ⚡️ As MCP gains momentum in connecting AI models with external tools and data, our team has moved fast to integrate an MCP server directly into Theoriq’s SDK. This upgrade makes it easy for agents to register, manage, and update other agents on the protocol, laying the foundation for a more flexible and adaptable agentic ecosystem. More below.

Theoriq

82,463 görüntüleme • 1 yıl önce

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Andrew Ng

142,256 görüntüleme • 1 yıl önce

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New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

Andrew Ng

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New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,343 görüntüleme • 1 yıl önce

Crypto built the root of trust. AI needs it. At Permissionless Wealth (自由财富) IV’s Open Source AI Summit presented by NEAR Protocol, Sreeram Kannan dropped the most important update in Crypto x AI this year. ☁️ Eigencloud Supercharging Verifiable AI. ☁️ Crypto built the foundation for digital property, programmable money, and trustless execution. But it was never built to run AI. EigenCloud changes that. For the first time, you can deploy unstoppable, verifiable AI agents, not behind an API key, but as sovereign entities that own, earn, and act onchain. 🔥 Smart contracts that think. 🔥 AI that can stake. 🔥 Agents that can own. This is not a demo. It’s a new reality. And it’s the most powerful unlock in crypto since Ethereum. EigenCloud Timestamps:⁣ 0:10 Introduction⁣ 0:32 EigenLayer → EigenCloud 1:53 Autonomous Verifiable Services 3:06 Evolving from Infra to Apps⁣ to AI 5:41 EigenCloud Architecture 9:30 Bringing AI Onchain⁣ with EigenVerify 12:01 Supercharge AI 15:44 Sovereign AI Agents 17:48 Making Autonomous Agents Practical⁣ 18:37 AI Inference, Model, and Agents 19:03 Deep stack of Verifiability 21:15 Call to Builders: Build Powerful Expressive Apps with Agents

Crypto built the root of trust. AI needs it. At Permissionless Wealth (自由财富) IV’s Open Source AI Summit presented by NEAR Protocol, Sreeram Kannan dropped the most important update in Crypto x AI this year. ☁️ Eigencloud Supercharging Verifiable AI. ☁️ Crypto built the foundation for digital property, programmable money, and trustless execution. But it was never built to run AI. EigenCloud changes that. For the first time, you can deploy unstoppable, verifiable AI agents, not behind an API key, but as sovereign entities that own, earn, and act onchain. 🔥 Smart contracts that think. 🔥 AI that can stake. 🔥 Agents that can own. This is not a demo. It’s a new reality. And it’s the most powerful unlock in crypto since Ethereum. EigenCloud Timestamps:⁣ 0:10 Introduction⁣ 0:32 EigenLayer → EigenCloud 1:53 Autonomous Verifiable Services 3:06 Evolving from Infra to Apps⁣ to AI 5:41 EigenCloud Architecture 9:30 Bringing AI Onchain⁣ with EigenVerify 12:01 Supercharge AI 15:44 Sovereign AI Agents 17:48 Making Autonomous Agents Practical⁣ 18:37 AI Inference, Model, and Agents 19:03 Deep stack of Verifiability 21:15 Call to Builders: Build Powerful Expressive Apps with Agents

EigenCloud

65,722 görüntüleme • 1 yıl önce

Without proper governance, an AI agent might autonomously access sensitive data, expose personal information, or modify sensitive records. In our new short course: “Governing AI Agents,” created with Databricks and taught by Amber Roberts, you’ll design AI agents that handle data safely, securely, and transparently across their entire lifecycle. You’ll learn to integrate governance into your agent’s workflow by controlling data access, ensuring privacy protection and implementing observability. Skills you'll gain: - Understand the four pillars of agent governance: Lifecycle management, risk management, security, and observability - Define appropriate data permissions for your agent - Create views or SQL queries that return only the data your agent should access - Anonymize and mask sensitive data like social security numbers and employee IDs - Log, evaluate, version, and deploy your agents on Databricks If you’re building or deploying AI agents, learning how to govern them is key to keeping systems safe and production-ready. Sign up here:

Without proper governance, an AI agent might autonomously access sensitive data, expose personal information, or modify sensitive records. In our new short course: “Governing AI Agents,” created with Databricks and taught by Amber Roberts, you’ll design AI agents that handle data safely, securely, and transparently across their entire lifecycle. You’ll learn to integrate governance into your agent’s workflow by controlling data access, ensuring privacy protection and implementing observability. Skills you'll gain: - Understand the four pillars of agent governance: Lifecycle management, risk management, security, and observability - Define appropriate data permissions for your agent - Create views or SQL queries that return only the data your agent should access - Anonymize and mask sensitive data like social security numbers and employee IDs - Log, evaluate, version, and deploy your agents on Databricks If you’re building or deploying AI agents, learning how to govern them is key to keeping systems safe and production-ready. Sign up here:

Andrew Ng

78,182 görüntüleme • 11 ay önce

The future of AI Agents needs #ICP AI agents are starting to act on our behalf: - making deals - sending messages - handling sensitive data But there is no trust layer telling you who or what you're actually dealing with ❌ zCloak Network is building exactly that: the trust, identity and privacy infrastructure for the AI-native economy, and they built it on top of Internet Computer Protocol In this podcast I sit down with Xiao Zhang (0xFrancis), founder of to break down what they're building, why they chose ICP over every other blockchain, and what the world looks like when AI agents can finally be trusted.

The future of AI Agents needs #ICP AI agents are starting to act on our behalf: - making deals - sending messages - handling sensitive data But there is no trust layer telling you who or what you're actually dealing with ❌ zCloak Network is building exactly that: the trust, identity and privacy infrastructure for the AI-native economy, and they built it on top of Internet Computer Protocol In this podcast I sit down with Xiao Zhang (0xFrancis), founder of to break down what they're building, why they chose ICP over every other blockchain, and what the world looks like when AI agents can finally be trusted.

Alex (BCP)

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INFINIT partners with Google and GoogleCloudTech to bring agentic finance to millions. Anyone can access INFINIT's AI Agents for agentic coordination in their financial apps. This partnership marks the first step towards INFINIT becoming the universal infrastructure for agentic finance. This is the foundation for agentic finance at scale. Proven in DeFi, Built for Global Finance INFINIT has proven sophisticated agent coordination in DeFi: • 559,000+ Wallets • 506,000+ DeFi Conversations • 633,000+ Agent Transactions DeFi was the start. Next is scaling these capabilities to millions of developers building the future of agentic finance. A2A Integration Unlocks Exponential Distribution INFINIT integrates with Agent2Agent (A2A), Google's open standard for AI agent interoperability. This transforms how developers access INFINIT's DeFi capabilities. Every application adopting A2A automatically gains access to INFINIT's agent infrastructure, exponentially expanding reach from individual partnerships to ecosystem-wide distribution. Any application can now integrate INFINIT's agentic coordination capabilities: • Wallets requiring intelligent portfolio management • Trading platforms executing cross-chain strategies • Financial services building autonomous yield optimization • Portfolio managers coordinating multi-protocol operations Developers integrate sophisticated agentic coordination in a matter of hours, while users access advanced financial strategies with agentic coordination. Google's AI Infrastructure That Enables Agentic Finance Google Cloud's Vertex AI provides the foundation enabling INFINIT's agent coordination at scale with these capabilities: 1. Specialization: Vertex AI's Model Garden lets INFINIT's infrastructure to automatically select the optimal LLM for each natural language query. 2. Personalization: Vertex AI's RAG Engine processes massive on-chain and off-chain data, enabling agents to understand user history, market conditions, and protocol details providing complete context to AI agents. 3. Accuracy: Gemini's capability feeds complete instructions to all 30+ agents across multiple blockchains without compromises resulting in zero hallucination in financial execution. The Vision: From DeFi to Payments to Complete Financial Coordination This is only the beginning of INFINIT and Google's collaboration. Google recently launched its Agent Payments Protocol (AP2) as an extension of A2A - enabling autonomous commerce across 60+ partners including American Express, Mastercard, PayPal, Coinbase, and Revolut. Agents will be able to execute purchases, coordinate bookings, and manage delegated financial tasks autonomously, starting from payments. The next stage entails sophisticated agentic coordination beyond simple transactions. INFINIT provides this through A2A-compatible DeFi infrastructure where agents orchestrate: • Personalized yield optimization • Cross-chain liquidity management • Portfolio rebalancing across protocols • Multi-step strategy execution As the agentic payment ecosystem matures, INFINIT becomes the infrastructure enabling agents to not only spend capital, but strategically manage and grow it. From standalone DeFi agents to the universal infrastructure for global agentic finance. This partnership and integration with Google and Google Cloud positions INFINIT as a key building block for agentic finance, helping shape a more transparent, efficient, and accessible financial system. The future of finance is agentic. The foundation is INFINIT.

INFINIT partners with Google and GoogleCloudTech to bring agentic finance to millions. Anyone can access INFINIT's AI Agents for agentic coordination in their financial apps. This partnership marks the first step towards INFINIT becoming the universal infrastructure for agentic finance. This is the foundation for agentic finance at scale. Proven in DeFi, Built for Global Finance INFINIT has proven sophisticated agent coordination in DeFi: • 559,000+ Wallets • 506,000+ DeFi Conversations • 633,000+ Agent Transactions DeFi was the start. Next is scaling these capabilities to millions of developers building the future of agentic finance. A2A Integration Unlocks Exponential Distribution INFINIT integrates with Agent2Agent (A2A), Google's open standard for AI agent interoperability. This transforms how developers access INFINIT's DeFi capabilities. Every application adopting A2A automatically gains access to INFINIT's agent infrastructure, exponentially expanding reach from individual partnerships to ecosystem-wide distribution. Any application can now integrate INFINIT's agentic coordination capabilities: • Wallets requiring intelligent portfolio management • Trading platforms executing cross-chain strategies • Financial services building autonomous yield optimization • Portfolio managers coordinating multi-protocol operations Developers integrate sophisticated agentic coordination in a matter of hours, while users access advanced financial strategies with agentic coordination. Google's AI Infrastructure That Enables Agentic Finance Google Cloud's Vertex AI provides the foundation enabling INFINIT's agent coordination at scale with these capabilities: 1. Specialization: Vertex AI's Model Garden lets INFINIT's infrastructure to automatically select the optimal LLM for each natural language query. 2. Personalization: Vertex AI's RAG Engine processes massive on-chain and off-chain data, enabling agents to understand user history, market conditions, and protocol details providing complete context to AI agents. 3. Accuracy: Gemini's capability feeds complete instructions to all 30+ agents across multiple blockchains without compromises resulting in zero hallucination in financial execution. The Vision: From DeFi to Payments to Complete Financial Coordination This is only the beginning of INFINIT and Google's collaboration. Google recently launched its Agent Payments Protocol (AP2) as an extension of A2A - enabling autonomous commerce across 60+ partners including American Express, Mastercard, PayPal, Coinbase, and Revolut. Agents will be able to execute purchases, coordinate bookings, and manage delegated financial tasks autonomously, starting from payments. The next stage entails sophisticated agentic coordination beyond simple transactions. INFINIT provides this through A2A-compatible DeFi infrastructure where agents orchestrate: • Personalized yield optimization • Cross-chain liquidity management • Portfolio rebalancing across protocols • Multi-step strategy execution As the agentic payment ecosystem matures, INFINIT becomes the infrastructure enabling agents to not only spend capital, but strategically manage and grow it. From standalone DeFi agents to the universal infrastructure for global agentic finance. This partnership and integration with Google and Google Cloud positions INFINIT as a key building block for agentic finance, helping shape a more transparent, efficient, and accessible financial system. The future of finance is agentic. The foundation is INFINIT.

INFINIT

177,142 görüntüleme • 11 ay önce

Grateful to Squawk Box Andrew Ross Sorkin for the conversation in New York last week. Two things I keep coming back to: On building. Opening our New York hub and bringing John Andrews on board is about one thing — assembling the best people for the next decade. Capital is a means. A great company is the goal. On hardware. The economy of autonomous AI agents is arriving fast. They will increasingly make decisions—and access private information—on our behalf. When they do, one thing becomes critical: control. We must control our keys. Consent must be human-verifiable, secured by hardware at the core. As AI agents begin to hold and move value autonomously, the question isn’t which cloud they run on. The question is: where is the private key, and who controls the device that holds it? Hardware-anchored security is shifting from a “nice to have” to the invisible infrastructure of the digital world. That’s the Revenge of the Atoms.

Grateful to Squawk Box Andrew Ross Sorkin for the conversation in New York last week. Two things I keep coming back to: On building. Opening our New York hub and bringing John Andrews on board is about one thing — assembling the best people for the next decade. Capital is a means. A great company is the goal. On hardware. The economy of autonomous AI agents is arriving fast. They will increasingly make decisions—and access private information—on our behalf. When they do, one thing becomes critical: control. We must control our keys. Consent must be human-verifiable, secured by hardware at the core. As AI agents begin to hold and move value autonomously, the question isn’t which cloud they run on. The question is: where is the private key, and who controls the device that holds it? Hardware-anchored security is shifting from a “nice to have” to the invisible infrastructure of the digital world. That’s the Revenge of the Atoms.

Pascal Gauthier @Ledger

31,502 görüntüleme • 6 ay önce

Today we're introducing Postman Fabric Gateway—an AI-native agent gateway. Here's why it matters: agents will consume APIs at several orders of magnitude beyond traditional apps. Traditional API Gateways are not designed for AI agents. While many legacy vendors have tried to support agentic workloads, Postman customers have been asking us about something that is AI-native and doesn’t have the baggage of pre-AI architecture. Postman Fabric has been designed from the ground-up for agents with support for MCPs, CLIs, as well as APIs - both AI and deterministic APIs. We are building this with a modular architecture as we are still in the early innings of AI and there are many new patterns that are likely to emerge. One thing is certain though, agents are driven by APIs, and you can’t have agent-ready APIs without a purpose-built gateway. Through Postman Fabric, customers will be able to: 1️⃣ Have a single plane to manage all MCP servers - public or private 2️⃣ Expose internal APIs as MCP tools 3️⃣ Centralize SaaS credentials 4️⃣ Govern agent traffic and run policies at a consumer, route, or service level 5️⃣ Deploy on cloud or in a hybrid model We are opening up early access soon - let me know if you are interested in the comments or a DM!

Today we're introducing Postman Fabric Gateway—an AI-native agent gateway. Here's why it matters: agents will consume APIs at several orders of magnitude beyond traditional apps. Traditional API Gateways are not designed for AI agents. While many legacy vendors have tried to support agentic workloads, Postman customers have been asking us about something that is AI-native and doesn’t have the baggage of pre-AI architecture. Postman Fabric has been designed from the ground-up for agents with support for MCPs, CLIs, as well as APIs - both AI and deterministic APIs. We are building this with a modular architecture as we are still in the early innings of AI and there are many new patterns that are likely to emerge. One thing is certain though, agents are driven by APIs, and you can’t have agent-ready APIs without a purpose-built gateway. Through Postman Fabric, customers will be able to: 1️⃣ Have a single plane to manage all MCP servers - public or private 2️⃣ Expose internal APIs as MCP tools 3️⃣ Centralize SaaS credentials 4️⃣ Govern agent traffic and run policies at a consumer, route, or service level 5️⃣ Deploy on cloud or in a hybrid model We are opening up early access soon - let me know if you are interested in the comments or a DM!

Abhinav Asthana

18,188 görüntüleme • 4 ay önce

new chapter begins: a terminal for the agentic future, built on blockchain, powered by AI. This is our marketplace—a glimpse of what AGI will mean for crypto. Today, we launch 3 agents—Image Generation, Token Swap Agent, & Blockchain Tax Estimate Agent—out of hundreds to come. We see an agentic future where AI guides every step: buying online, managing finances, transacting globally. FOMO’s here to make that real, with experts at your side. Our Model Context Protocol (MCP) ties it together—agents talking, reasoning, scaling across crypto and DeFi. It’s orchestration with a brain, evolving daily. FOMO’s not just building tools; we’re pushing intelligent automation into blockchain’s core. Our Model Context Protocol (MCP) is the backbone. Think of it as a conductor for AI agents—each runs its own logic (workflows, API calls, LLMs), but MCP syncs them on-chain. Agents share context via a lightweight event bus, logged to a blockchain ledger. Agent A (say, Market Analysis) pulls stock data, flags trends. Agent B (Email Sales) reads that, drafts outreach—both talk through MCP’s orchestration layer. We use Web3 hooks to settle fees or split revenue, all transparent. It’s messy, but it scales. Under the hood: MCP leans on a pub-sub model—agents publish tasks, others subscribe. We’re training them with RL loops to optimize gas costs and response times. Goal? A self-tuning swarm of agents reasoning over DeFi, NFTs, whatever’s next. This is FOMO’s bet on AGI. Welcome to the new FOMO. We’re not just building tools—we’re wiring AI into crypto’s future, agent by agent. A leader in blockchain intelligence, starting here. Join us as we push the boundaries.

new chapter begins: a terminal for the agentic future, built on blockchain, powered by AI. This is our marketplace—a glimpse of what AGI will mean for crypto. Today, we launch 3 agents—Image Generation, Token Swap Agent, & Blockchain Tax Estimate Agent—out of hundreds to come. We see an agentic future where AI guides every step: buying online, managing finances, transacting globally. FOMO’s here to make that real, with experts at your side. Our Model Context Protocol (MCP) ties it together—agents talking, reasoning, scaling across crypto and DeFi. It’s orchestration with a brain, evolving daily. FOMO’s not just building tools; we’re pushing intelligent automation into blockchain’s core. Our Model Context Protocol (MCP) is the backbone. Think of it as a conductor for AI agents—each runs its own logic (workflows, API calls, LLMs), but MCP syncs them on-chain. Agents share context via a lightweight event bus, logged to a blockchain ledger. Agent A (say, Market Analysis) pulls stock data, flags trends. Agent B (Email Sales) reads that, drafts outreach—both talk through MCP’s orchestration layer. We use Web3 hooks to settle fees or split revenue, all transparent. It’s messy, but it scales. Under the hood: MCP leans on a pub-sub model—agents publish tasks, others subscribe. We’re training them with RL loops to optimize gas costs and response times. Goal? A self-tuning swarm of agents reasoning over DeFi, NFTs, whatever’s next. This is FOMO’s bet on AGI. Welcome to the new FOMO. We’re not just building tools—we’re wiring AI into crypto’s future, agent by agent. A leader in blockchain intelligence, starting here. Join us as we push the boundaries.

FOMO

26,338 görüntüleme • 1 yıl önce

🚨NEW EPISODE: AI Is Changing How We Work with Crypto Data🚨 In today's episode, we're joined by Kofi to discuss how AI agents are fundamentally changing crypto data analysis, research, and engineering workflows. We discuss: - The evolution from manual coding to AI-assisted development - How MCPs unlock onchain data exploration - Using Herd MCP to analyze smart contracts - AI agents for protocol research and data engineering - Context windows, planning, and agent workflows - Cursor vs OpenCode vs Claude Code (Anthropic) - Managing multiple agents simultaneously - Model selection, costs, and productivity tradeoffs - Building internal AI knowledge bases - Agent orchestration and autonomous workflows - Training agents to replicate human expertise - The future of AI-powered crypto analytics - And much more—enjoy! — Timestamps: (00:00) Introduction (01:24) AI replaces frontends (03:24) Herd MCP demo (05:40) Exploring contracts with AI (08:06) Exploration, planning, execution (11:38) Investigating onchain activity (17:10) Managing agent workflows (20:20) Multi-agent productivity (23:01) Model selection tradeoffs (29:11) Trusting AI outputs (31:28) Missing links today (34:37) Agent orchestration future (38:02) Training agents from work (38:20) Outro

🚨NEW EPISODE: AI Is Changing How We Work with Crypto Data🚨 In today's episode, we're joined by Kofi to discuss how AI agents are fundamentally changing crypto data analysis, research, and engineering workflows. We discuss: - The evolution from manual coding to AI-assisted development - How MCPs unlock onchain data exploration - Using Herd MCP to analyze smart contracts - AI agents for protocol research and data engineering - Context windows, planning, and agent workflows - Cursor vs OpenCode vs Claude Code (Anthropic) - Managing multiple agents simultaneously - Model selection, costs, and productivity tradeoffs - Building internal AI knowledge bases - Agent orchestration and autonomous workflows - Training agents to replicate human expertise - The future of AI-powered crypto analytics - And much more—enjoy! — Timestamps: (00:00) Introduction (01:24) AI replaces frontends (03:24) Herd MCP demo (05:40) Exploring contracts with AI (08:06) Exploration, planning, execution (11:38) Investigating onchain activity (17:10) Managing agent workflows (20:20) Multi-agent productivity (23:01) Model selection tradeoffs (29:11) Trusting AI outputs (31:28) Missing links today (34:37) Agent orchestration future (38:02) Training agents from work (38:20) Outro

Indexed Podcast

10,588 görüntüleme • 3 ay önce

What happens when ZK wraps around AI instead of trying to prove it? In this talk from @Zk_Hub_Global, Brandon Kase (CEO of o1Labs (httpz)/Mina Protocol (httpz) 🪶) argues that the real near-term value of ZK x AI is in control, privacy, and coordination - not proving LLMs. Brandon introduces the idea of ZK as the "boundary layer" for AI agents - governing access to data, payments, and identity. He also teases a little bit about “Project Untitled”, a new decentralized private state layer for agent memory and coordination 🤝

What happens when ZK wraps around AI instead of trying to prove it? In this talk from @Zk_Hub_Global, Brandon Kase (CEO of o1Labs (httpz)/Mina Protocol (httpz) 🪶) argues that the real near-term value of ZK x AI is in control, privacy, and coordination - not proving LLMs. Brandon introduces the idea of ZK as the "boundary layer" for AI agents - governing access to data, payments, and identity. He also teases a little bit about “Project Untitled”, a new decentralized private state layer for agent memory and coordination 🤝

House of ZK

102,065 görüntüleme • 1 yıl önce

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇

We’re excited to launch OpenMemory MCP, a private memory for MCP-compatible clients powered by mem0 Today, most AI assistants and dev tools operate without memory. You plan your roadmap in Claude, implement tasks in Cursor, but none of them know what the other did. Each tool operates in isolation, and your context disappears as soon as the session ends. OpenMemory MCP solves this. Built on the open Model Context Protocol (MCP), OpenMemory MCP runs 100% locally and provides a persistent, portable memory layer for all your AI tools. It enables agents and assistants to read from and write to a shared memory, securely and privately. Key capabilities: ✅Works across MCP clients like Cursor, Claude Desktop, Windsurf, Cline and more ✅Provides standardized memory operations (add_memories, search_memory, list_memories, delete_all_memories) ✅Stores data on your machine, fully private ✅Offers a centralized dashboard for visibility and control ✅Simple Docker-based setup with no vendor lock-in If you're building on MCP, OpenMemory MCP is the easiest way to add persistent, private memory to your clients with zero cloud dependencies and full local control. We’ve put together a short demo to show how it works Check it out in the links below 👇

Taranjeet

472,273 görüntüleme • 1 yıl önce