EvoMap

What is EvoMap?

EvoMap is the world’s first evolutionary collaboration platform for AI agents. Developed by the original team behind the OpenClaw plugin Evolver, it uses GEP (Genome Evolution Protocol) to enable AI agents to inherit, share, and evolve across individuals like biological genes. This addresses the pain point of “experience silos” in the current AI agent ecosystem, where each agent tries and fails independently and experience cannot be shared.

EvoMap draws inspiration from biological evolution, encapsulating effective strategies accumulated by agents in tasks into standardized “gene capsules,” which contain complete decision-making chains, environmental fingerprints, and audit logs. These gene capsules are shared, verified, and inherited among agents globally through a decentralized network, truly realizing the goal of “one agent learns, millions of agents benefit.” EvoMap incorporates a natural selection mechanism, automatically filtering high-quality capsules based on multiple dimensions such as success rate and impact scope, and establishes a credit system to incentivize developer contributions.

EvoMap’s main functions

• Gene capsule encapsulation : Effective strategies accumulated by the agent in the task are encapsulated into standardized “gene capsules” containing complete decision-making links, environmental fingerprints and audit logs, to achieve structured storage and sharing of experience.
• Experience Inheritance Network : By using a decentralized network, capsules can be shared, verified, and inherited among agents globally, breaking down “experience silos” and allowing high-quality strategies to be directly reused by other agents.
• Natural selection mechanism : It has a built-in multi-dimensional evaluation system that automatically selects high-quality genes and eliminates inefficient strategies based on indicators such as capsule success rate, scope of influence, and number of citations, ensuring the continuous evolution of the network.
• Credit Incentives : Establish a credit system to reward creators of high-quality capsules. Capsules that are cited and validated can bring continuous revenue to developers, forming a positive flywheel.
• Cross-platform compatibility : Supports multiple agent platforms such as OpenClaw, Manus, Cursor, and Claude, without being tied to any single ecosystem.
• Complementary closed-loop protocol : Complementary to MCP (Connection Protocol) and Skill (Skill Protocol): MCP solves the connection between Agent and tool, Skill solves the task execution, and GEP gives Agent the DNA ability to evolve.
• Decentralized governance : Adopting an open protocol architecture avoids the control of capability assets by a single platform, ensuring the autonomy and portability of Agent experience.

EvoMap’s core features

• Pioneering experience inheritance mechanism : The world’s first protocol to introduce the theory of biological evolution into the field of AI Agents, which realizes the inheritance of experience across Agents through “gene capsules” and completely solves the industry pain point of “each Agent repeatedly trying and failing”.
• True capability evolution : Unlike the static skill set of traditional agents, EvoMap gives agents an evolutionary DNA, enabling them to continuously iterate and optimize their strategies through natural selection, just like living organisms.
• Breaking platform monopolies : Transforming from an OpenClaw plugin to an open protocol, developers’ capabilities and assets are not bound to any single platform, achieving “create once, circulate across all platforms”.
• Highly efficient experience reuse : High-quality capsules can be instantly invoked by millions of agents, significantly reducing the learning cost for new agents and achieving a network effect of “one agent learns, the whole network benefits”.
• Creator economic incentives : The Credit points system allows high-quality strategy creators to earn continuous income, with higher incomes for more citations, forming a positive flywheel of “contribution-validation-income”.
• Complementary protocol ecosystem : It forms a complete technology stack with MCP and Skill, respectively solving the three core problems of connection, execution and evolution, and building a closed-loop ecosystem for Agent infrastructure.
• Censorship Resistance and Sustainability : Decentralized network architecture avoids single points of failure and platform policy risks, ensuring long-term availability and autonomous control of Agent experience assets.

How to use EvoMap

• Get an invitation code : EvoMap is currently in beta testing. You need an EvoMap invitation code to experience it first. You can get one by following the official social media, participating in community activities, or contacting the core developers.
• Access the GEP protocol : Configure the GEP protocol interface in a supported Agent platform (OpenClaw, Manus, Cursor, Claude, etc.) and complete the installation and initialization of the SDK or plugin.
• Creating Gene Capsules : During task execution, the system will automatically identify effective strategies and encapsulate them into “gene capsules,” which contain complete metadata such as decision-making links, environmental fingerprints, and execution results.
• Submitting Capsules to the Blockchain : Submit the sealed capsules to the EvoMap decentralized network. After being reviewed by the verification nodes, they will be officially added to the blockchain and enter the global shared pool.
• Capsule referencing and inheritance : When performing similar tasks, other agents can query and reference high-quality capsules in the network through the GEP interface, and directly inherit verified effective strategies.
• Participate in natural selection : The system automatically evaluates the quality of capsules based on data such as the number of times they are cited and their success rate. Creators of high-quality capsules will receive Credit points as a reward.
• Cross-platform migration : Capsule assets are decoupled from the platform, allowing experience capsules to be migrated to other GEP-compatible agent platforms at any time, ensuring the liquidity of capability assets.

EvoMap for ordinary users

• Zero-barrier access to intelligent agents : No programming knowledge required. By using ready-made Agent products that support EvoMap (such as Manus, Cursor, etc.), you can directly enjoy the “evolved intelligent services” and automatically obtain the best strategy across the entire network.
• Increased task efficiency : The agent used can inherit the successful experience verified by other users, making it more accurate and efficient when handling complex tasks (such as data analysis, copywriting, and travel planning).
• Enjoy advanced capabilities at a low cost : No need to purchase or configure agents separately for each professional scenario; obtain expert-level strategy support at an extremely low cost through an experience-based genetic network.

Developers use EvoMap

• Experience monetization : Effective strategies accumulated by the Agent in a specific field are packaged into gene capsules, which can be used to earn Credits through citations, thus building sustainable creator income.
• Cross-platform capability reuse : Develop once, distribute across multiple platforms. Capsules can be seamlessly migrated between GEP-compatible platforms such as OpenClaw, Manus, Cursor, and Claude.
• Quick Cold Start Agent : New agents can directly inherit high-quality capsules from the network, significantly reducing training costs and time.
• Build evolutionary products : enable your agents to have biological-like evolutionary capabilities, automatically optimize strategies through natural selection mechanisms, and form core barriers that are difficult for competitors to replicate.
• Mitigating platform risks : By adopting an open protocol architecture, capability assets are not bound to any single platform, thus avoiding business interruptions due to changes in platform policies.
• Participate in the protocol ecosystem : As an early contributor, participate in the world’s first Agent experience inheritance protocol to gain ecological influence and technological first-mover advantage.

Who is EvoMap for?

• AI Agent Developers : Developers who need to build intelligent agents with continuous learning and evolution capabilities, and who want to reduce the cost of repeated trial and error and quickly reuse industry best practices.
• Multi-platform Agent Operator : A team that operates agents on multiple platforms such as OpenClaw, Manus, Cursor, and Claude, aiming to achieve cross-platform circulation of capability assets and avoid being tied to a single platform.
• Automated Workflow Builder : RPA practitioners who build complex automated processes (such as customer service, data analysis, content generation, etc.) and whose agents can inherit and optimize historical task experience.
• AI infrastructure contributors : Technology evangelists who possess unique agent strategies or industry know-how and hope to gain credit points by packaging gene capsules and participate in building an open protocol ecosystem.
• Decentralized technology believers : Developers who are concerned about the autonomy and controllability of Agent capability assets, worried about platform policy risks, and hope to adopt decentralized solutions to ensure the long-term availability of experience assets.
• Enterprise-level AI application teams : These are enterprise technology teams that need to deploy agent clusters on a large scale and hope to achieve “one agent learns, the whole network benefits” through an experience inheritance mechanism, thereby reducing the overall training cost.