Chapter 1 AI+Crypto: Dual Waves Accelerating Convergence
Since 2024, we have heard the phrase AI+Crypto more and more frequently. From the emergence of ChatGPT, to the launch of multimodal super models by emerging model institutions such as OpenAI, Anthropic, and Mistral, to the various DeFi protocols, governance systems, and even NFT social platforms in the on-chain world trying to connect to AI Agents, the integration of this double technology wave is no longer a distant imagination, but a new paradigm evolution that is happening in reality.
The fundamental driving force of this trend comes from the mutual complementation of the two major technology systems on the demand side and the supply side. The development of AI makes it possible to migrate task execution and information processing from humans to machines, but it still faces fundamental limitations such as lack of contextual understanding, lack of incentive structure, and untrusted output. The on-chain data system, incentive design mechanism, and programmatic governance framework provided by Crypto can make up for these shortcomings of AI. In turn, the Crypto industry is also in urgent need of stronger intelligent tools to handle highly repetitive tasks such as user behavior, risk management, and transaction execution, which is exactly the area where AI excels.
In other words, Crypto provides a structured world for AI, while AI injects active decision-making capabilities into Crypto. This fusion of mutually underlying technologies has formed a new pattern of deep mutual infrastructure. A notable example is the emergence of AI Market Makers in the DeFi protocol. This type of system uses AI models to model market fluctuations in real time, and combines variables such as on-chain data, order book depth, and cross-chain sentiment indicators to achieve dynamic liquidity scheduling, thereby replacing traditional static fixed parameter models. For example, in the governance scenario, the AI-assisted Governance Agent began to try to parse the content of proposals, user intentions, predict voting tendencies, and push personalized decision-making recommendations to users. In this scenario, AI is not just a tool, but has gradually evolved into an on-chain cognitive executor.
Moreover, from a data perspective, on-chain behavioral data is inherently verifiable, structured, and censorship-resistant, making it an ideal training material for AI models. Some emerging projects (such as Ocean Protocol and Bittensor) have already tried to embed on-chain behaviors into the model fine-tuning process, and in the future there may even be an on-chain AI model standard that enables the model to have native Web3 semantic understanding capabilities during training.
At the same time, the on-chain incentive mechanism also provides AI systems with a more sound and sustainable economic impetus than the Web2 platform. For example, through the Agent Incentive Protocol defined by the MCP protocol, model executors no longer rely on API call billing, but can obtain token rewards through the on-chain proof of task execution + user intention fulfillment + traceable economic value. In other words, for the first time, AI agents can participate in the economic system instead of just being embedded in it as a tool.
From a more macro perspective, this trend is not only a technological convergence, but also a paradigm shift. AI+Crypto may eventually evolve into an Agent-centered on-chain social structure: humans are no longer the only governors, and the model can not only execute contracts on the chain, but also understand the context, coordinate games, actively govern, and establish its own micro-economy through token mechanisms. This is not science fiction, but a reasonable deduction based on the current technological trajectory.
Because of this, the AI+Crypto narrative has rapidly gained high attention from the capital market in the past six months. From a16z, Paradigm to Multicoin, from Eigenlayers validator market to Bittensors model mining, and to the recent launch of projects such as Flock and Base MCP, we see a consensus gradually forming: AI models will play a role in Web3 that is not just a tool, but a subject - they will have identity, context, incentives, and even governance rights.
It is foreseeable that in the Web3 world after 2025, AI agents will be unavoidable system participants. This participation mode is not the traditional access of off-chain model + on-chain API, but gradually evolves into a new form of model as node and intention as contract. Behind this is the semantics and execution paradigm constructed by new protocols such as MCP (Model Context Protocol).
The integration of AI and Crypto is one of the few “bottom-to-bottom connection” opportunities in the past decade. This is not a hot spot that explodes at a single point, but a long-term, structural evolution. It will determine how AI operates, how it is coordinated, and how it is motivated on the chain, and will ultimately define the future form of the social structure on the chain.
Chapter 2 Background and core mechanism of MCP protocol
The integration of AI and cryptography is moving from the conceptual exploration stage to a critical period of practical verification. Especially since 2024, after large models represented by GPT-4, Claude, and Gemini have begun to have stable context management, complex task decomposition, and self-learning capabilities, AI is no longer just providing off-chain intelligence, but gradually has the possibility of continuous interaction and autonomous decision-making on the chain. At the same time, the crypto world itself is also undergoing structural evolution. The maturity of technologies such as Modular Blockchain, Account Abstraction, and Rollup-as-a-Service has greatly improved the flexibility of on-chain execution logic, clearing environmental barriers for AI to become a native participant in the blockchain.
In this context, MCP (Model Context Protocol) was proposed, with the goal of building a universal protocol layer for a complete set of AI models to run, execute, feedback and benefit on the chain. This is not only to solve the technical problem of AI cannot be used efficiently on the chain, but also to respond to the systematic needs of the Web3 world itself to transition to the Intent-centric Paradigm. The traditional smart contract call logic requires users to have a high understanding of the chains status, function interface, and transaction structure, which is a huge gap from the natural expression of ordinary users. The intervention of AI models can bridge this structural rupture, but for AI models to work, they must have identity, memory, authority and economic incentives on the chain. The MCP protocol was born to solve this series of bottlenecks.
Specifically, MCP is not an independent model or platform, but a full-chain semantic layer protocol that runs through AI model calling, context building, intent understanding, on-chain execution, and incentive feedback. The core of its design revolves around four levels: First, the establishment of the model identity mechanism. Under the MCP framework, each model instance or agent has an independent on-chain address, and can receive assets, initiate transactions, and call contracts through the permission verification mechanism, thus becoming the first-class account in the blockchain world. The second is the context collection and semantic interpretation system. This module abstracts the on-chain status, off-chain data, and historical interaction records, combined with natural language input, to provide the model with a clear task structure and environmental background, so that it has the semantic context to execute complex instructions.
Currently, many projects have begun to build prototype systems around the MCP concept. For example, Base MCP is trying to deploy AI models as publicly callable on-chain agents to serve scenarios such as trading strategy generation and asset management decisions; Flock has built a multi-agent collaboration system based on the MCP protocol, allowing multiple models to dynamically collaborate around the same user task; and projects such as LyraOS and BORK are further trying to expand MCP into the basic layer of the model operating system, on which any developer can build model plug-ins with specific capabilities and make them available for others to call, thereby forming a shared on-chain AI service market.
From the perspective of crypto investors, the introduction of MCP brings not only a new technological path, but also an opportunity to reshape the industrial structure. It opens up a new native AI economic layer, where models are not only tools, but also participants in the economy with accounts, credit, income and evolution paths. This means that in the future, market makers in DeFi may be models, voting participants in DAO governance are models, content curators in the NFT ecosystem are models, and even the on-chain data itself is parsed, combined and repriced by the model, thus deriving a new AI behavioral data asset. Therefore, investment thinking will also shift from investing in an AI product to investing in an incentive center, service aggregation layer or cross-model coordination protocol in an AI ecological layer. As the underlying semantics and execution interface protocol, MCPs potential network effects and standardization premium are very worthy of medium- and long-term attention.
As more and more models enter the Web3 world, the closed loop of identity, context, execution and incentives will determine whether this trend can be truly implemented. MCP is not a single breakthrough, but an infrastructure-level protocol that provides a consensus interface for the entire AI+Crypto wave. It attempts to answer not only the technical question of how to put AI on the chain, but also the economic question of how to motivate AI to continue to create value on the chain.
Chapter 3 Typical landing scenarios of AI Agent: How MCP reconstructs the on-chain task model
When the AI model truly has an on-chain identity, semantic context awareness, the ability to parse intent and perform on-chain tasks, it is no longer just an auxiliary tool, but a real on-chain agent, becoming the active entity that executes logic. This is precisely the greatest significance of the existence of the MCP protocol - it is not to make a certain AI model stronger, but to provide a structured path for AI models to enter the blockchain world, interact with contracts, collaborate with people, and interact with assets. This path not only includes underlying capabilities such as identity, permissions, and memory, but also includes operational intermediate layers such as task decomposition, semantic planning, and proof of performance, and ultimately leads to the possibility of AI Agents actually participating in the construction of the Web3 economic system.
Starting from the most practical application, on-chain asset management is the first field that AI Agent penetrates. In the past DeFi, users need to manually configure wallets, analyze liquidity pool parameters, compare APY, and set strategies. The whole process is extremely unfriendly to ordinary users. The AI Agent based on MCP can automatically crawl on-chain data after obtaining intentions such as optimizing yield or controlling risk exposure, judge the risk premium and expected volatility of different protocols, and dynamically generate trading strategy combinations, and then verify the security of the execution path through simulation calculations or on-chain real-time backtesting. This model not only improves the personalization and response speed of strategy generation, but more importantly, it enables non-professional users to entrust assets in natural language for the first time, making asset management no longer a behavior with extremely high technical barriers.
Another scenario that is maturing rapidly is on-chain identity and social interaction. Previous on-chain identity systems were mostly based on transaction history, asset holdings, or specific proof mechanisms (such as POAP), and their expressiveness and plasticity were extremely limited. When AI models are involved, users can have a semantic agent that is constantly synchronized with their preferences, interests, and behavioral dynamics. This agent can participate in social DAOs, publish content, plan NFT activities, and even help users maintain their reputation and influence on the chain. For example, some social chains have begun to deploy agents that support the MCP protocol to automatically assist new users in completing the Onboarding process, building social graphs, and participating in comments and voting, thereby transforming the cold start problem from a product design problem to an intelligent agent participation problem. Furthermore, in the future when identity diversity and personality bifurcation are widely accepted, a user may have multiple AI agents for different social situations, and MCP will become the identity governance layer that manages the code of conduct and execution authority of these agents.
The third key point of AI Agent is governance and DAO management. In the current DAO, activity and governance participation rate are always bottlenecks, and the voting mechanism also has strong technical barriers and behavioral noise. After the introduction of MCP, agents with semantic parsing and intent understanding capabilities can help users regularly sort out DAO dynamics, extract key information, and semantically summarize proposals, and recommend voting options or automatically execute voting behaviors based on understanding user preferences. This on-chain governance based on the preference agent mechanism greatly alleviates the problems of information overload and incentive mismatch. At the same time, the MCP framework also allows governance experience and strategy evolution paths to be shared between models. For example, if an agent observes negative externalities caused by a certain type of governance proposal in multiple DAOs, it can feed back the experience to the model itself, forming a cross-community governance knowledge migration mechanism, thereby building an increasingly intelligent governance structure.
In addition to the above mainstream applications, MCP also provides a unified interface possibility for AI in scenarios such as on-chain data curation, game world interaction, ZK automatic proof generation, and cross-chain task relay. In the field of blockchain games (GameFi), AI Agent can become the brain behind non-player characters (NPCs), realizing real-time dialogue, plot generation, task scheduling, and behavior evolution; in the NFT content ecosystem, the model can serve as a semantic curator to dynamically recommend NFT collections based on user interests, and even generate personalized content; in the ZK field, the model can quickly translate intent into a ZK-friendly constraint system through structured compilation, simplifying the zero-knowledge proof generation process and improving the universality of the development threshold.
From the commonalities of these applications, it is clear that what the MCP protocol is changing is not the single-point performance of a certain application, but the paradigm of task execution itself. Traditional Web3 task execution is based on the premise of you know how to do it - users must have a clear grasp of the underlying knowledge such as contract logic, transaction structure, and network fees. MCP transforms this paradigm into you just need to express what you want to do and the model will do the rest. The interactive middle layer between users and chains has changed from a code interface to a semantic interface, and from function calls to intent orchestration. This fundamental change has promoted AI from a tool to a behavior subject and has also transformed blockchain from a protocol network to an interactive context.
Chapter 4: In-depth analysis of the market prospects and industry applications of the MCP protocol
As a cutting-edge innovation that integrates AI and blockchain technology, the MCP protocol not only brings a new economic model to the crypto market, but also provides new development opportunities for multiple industries. With the continuous advancement of AI technology and the continuous expansion of blockchain application scenarios, the market prospects of the MCP protocol will gradually show its huge potential. This chapter will deeply analyze the application prospects of the MCP protocol in multiple industries, and conduct in-depth discussions from the aspects of market dynamics, technological innovation, and industrial chain integration.
4.1 Market potential of AI+Crypto integration
The integration of AI and blockchain has become an important force in promoting the digital transformation of the global economy. Especially under the impetus of the MCP protocol, AI models can not only perform tasks, but also exchange value on the blockchain and become an independent economy. With the continuous development of AI technology, more and more AI models are beginning to undertake actual market tasks and participate in multiple fields such as commodity production, service delivery, and financial decision-making. At the same time, the decentralization, transparency, and immutability of blockchain provide an ideal trust mechanism for AI models, enabling them to be quickly implemented and applied in a variety of industries.
It is expected that the integration of AI and the crypto market will usher in explosive growth in the next few years. As one of the pioneers of this trend, the MCP protocol will gradually occupy an important position, especially in the fields of finance, medical care, manufacturing, smart contracts and digital asset management. The emergence of AI-native assets has not only created abundant opportunities for developers and investors, but also brought unprecedented disruptive impacts to traditional industries.
4.2 Diversification of market applications and cross-border collaboration
The MCP protocol brings possible cross-border integration and collaboration to multiple industries. Especially in industries such as finance, healthcare, and the Internet of Things, the application of the MCP protocol will greatly promote innovation and development in various fields. In the financial industry, the MCP protocol can promote the deepening of the DeFi ecosystem by providing tradable income rights assets for AI models. Users can not only invest in the AI model itself, but also trade the models income rights on the decentralized financial platform through smart contracts. The emergence of this model provides investors with more abundant investment options and may drive more traditional financial institutions to expand into the blockchain and AI fields.
In the medical field, the MCP protocol can support the application of AI in precision medicine, drug development, and disease prediction. AI models analyze large amounts of medical data to generate disease prediction models or drug development directions, and collaborate with medical institutions through smart contracts. This collaboration can not only improve the efficiency of medical services, but also provide transparent and fair solutions in terms of data privacy protection and results distribution. The incentive mechanism of the MCP protocol ensures that the rights and interests of AI models and medical service providers are equally distributed, thereby encouraging the emergence of more innovative technologies.
Applications in the field of Internet of Things (IoT), especially in the construction of smart homes and smart cities, will also benefit from the MCP protocol. AI models can provide intelligent decision support for IoT devices through real-time analysis of sensor data. For example, AI can optimize energy consumption based on environmental data, improve the efficiency of collaboration between devices, and reduce the cost of the overall system. The MCP protocol provides a reliable incentive and reward mechanism for these AI models, ensuring the enthusiasm of all parties to participate, thereby promoting the further development of the Internet of Things.
4.3 Technological innovation and industrial chain integration
The market prospects of the MCP protocol lie not only in its own technological breakthroughs, but also in its ability to promote the integration and collaboration of the entire industry chain. In the combination of blockchain and AI, the MCP protocol will promote the deep integration of the industrial chain, break down traditional industry barriers, and promote cross-industry resource integration. For example, in terms of sharing AI training data and optimizing algorithms, the MCP protocol can provide a decentralized platform that enables all parties to share computing resources and training data without having to rely on traditional centralized institutions. Through decentralized trading methods, the MCP protocol helps break the data island phenomenon in traditional industries and promote the flow and sharing of data.
In addition, the MCP protocol will further promote the open source and transparency of technology. Through blockchain-based smart contracts, developers and users can customize and optimize AI models on their own. The decentralized nature of the MCP protocol enables innovators and developers to collaborate and share technological achievements in an open ecosystem, which provides important support for technological progress and innovation in the entire industry. At the same time, the combination of blockchain and AI has also expanded the application scenarios of technology. From finance to manufacturing, from medical care to education, the MCP protocol has a broad application space.
4.4 Investment perspective: future capital markets and commercialization potential
As the MCP protocol becomes more popular and mature, investors will continue to pay more attention to this field. The MCP protocol provides investors with a variety of ways to participate through a decentralized reward mechanism and assetized model income rights. Investors can directly purchase the income rights of the AI model and obtain returns through the market performance of the model. In addition, the token economic design in the MCP protocol also provides new investment products for the capital market. In the future digital asset market, AI model assets based on the MCP protocol may become an important investment target, attracting various capitals including venture capital, hedge funds and individual investors to enter this market.
The participation of the capital market will not only promote the popularity of the MCP protocol, but also accelerate its commercialization process. Enterprises and developers can obtain financial support for further development and optimization of AI models by financing, selling or licensing the revenue rights of AI models. In this process, the flow of capital will become an important force to promote technological innovation, market application and industrial expansion. Investors confidence in the MCP protocol will directly affect its position and commercial value in the global market.
Chapter 5 Conclusion and Future Outlook
The MCP protocol represents an important direction for the integration of AI and the crypto market, especially in decentralized finance (DeFi), data privacy protection, smart contract automation, and AI assetization. It has shown great development potential. As AI technology becomes more and more sophisticated, more and more industries will gradually realize AI empowerment, and the MCP protocol provides a decentralized, transparent, and traceable operating platform for these AI models. Under this framework, not only can the efficiency and value of AI models be improved, but also it can bring them wide market acceptance.
In the past few years, blockchain technology and artificial intelligence (AI) have gradually moved from their own independent fields to integration. With the continuous development of technology, the combination of AI and blockchain not only provides new solutions for various industries, but also promotes the birth of new business models. The MCP protocol came into being against this background. It has brought unprecedented innovation to the crypto market by introducing decentralization and incentive mechanisms and leveraging the complementary advantages of AI and blockchain. As AI and blockchain technologies continue to mature, the MCP protocol will not only reshape the ecosystem of the digital asset economy, but also provide new impetus for the transformation of the global economy.
From an investment perspective, the application of the MCP protocol will attract a large amount of capital inflow, especially venture capital and hedge funds that pursue innovative investment opportunities. As more and more AI models can be assetized, traded, and value-added through the MCP protocol, the market demand derived from it will further promote the popularity of the protocol. In addition, the decentralized nature of the MCP protocol means that it can avoid the single point of failure of centralized systems, thereby enhancing its long-term stability in the global market.
In the future, as the ecosystem of the MCP protocol becomes increasingly rich, AI and crypto assets based on the protocol may become mainstream investment tools in the digital currency and financial markets. These AI assets can not only become value-added tools in the crypto market, but may also develop into important financial products worldwide, promoting the formation of a new global economic landscape.
