Agent Creation in Shinkai

Agent creation is at the heart of Shinkai, making it easy for anyone to build customized AI agents that handle real-world tasks autonomously. For common users, it's like assembling a smart assistant without coding—pick a name, add instructions, and equip it with tools. For ecosystem supporters and exchanges, this democratizes AI development, enabling scalable, monetizable ecosystems where agents can generate revenue through services like arbitrage or content summarization, all secured by blockchain integrations.

What Is Agent Creation and Why Does It Matter?

In Shinkai, an "agent" is a specialized AI that goes beyond chatbots: it can plan, remember context, call tools (like APIs or local files), and even collaborate with other agents. Creation is no-code, so you don't need programming skills—just describe what you want, and Shinkai handles the rest. This turns AI into practical tools for everyday needs, like a "YouTube Expert" that searches videos, extracts transcripts, and summarizes them, or a "Solana Arbitrage Agent" that spots trading opportunities and executes via Jupiter DEX—all running on schedule without your intervention.

  • Benefits for Users: Quick setup for personal workflows; privacy-focused (runs locally with Ollama models or mixes remote ones like Grok/Claude). Agents remember past interactions and generate files for shared context.
  • Benefits for Ecosystem Supporters/Exchanges: Fosters a vibrant marketplace; creators can monetize agents via fees (e.g., $0.002 USDC per call) or resell unused API credits. Composable agents drive network growth, with crypto-native security for DeFi tasks (keys never leave your device).

Shinkai supports over 300 local models (GGUF format from Hugging Face) and remote options, giving flexibility for cost vs. performance.

How to Create and Customize an Agent

Start in the Shinkai app's Agents section: It's intuitive and takes minutes.

  1. Name and Describe: Give your agent a name (e.g., "Negotiation Expert") and description. Add system instructions (e.g., "Draw from William Ury and Roger Fisher for advice").
  2. Add Knowledge and Tools: Upload files (PDFs, markdown) for context. Equip tools—like YouTube API for searches or CoinGecko for prices.
  3. Test and Tweak: A side panel lets you chat with the agent in real-time. Adjust parameters (temperature, top-k) or fork conversations to explore alternatives.
  4. Schedule and Deploy: Set it to run autonomously (e.g., arbitrage checks every 10 minutes). For decentralized sharing, link a wallet and expose it via MCP.

Once saved, agents can generate their own files, use prompt libraries, or integrate with local systems.

Here's a flowchart for the basic creation process:

Advanced Concepts: Tool Generation and Integrations

For power users, Shinkai offers deeper features. Tools are key—agents call them for actions like API queries or blockchain trades. Create tools two ways:

  • Shinkai Core Code Generator: An AI specialized in protocols (e.g., YouTube, Uniswap, CoinGecko). It auto-generates tools, similar to Versal v0 but tailored for agents.
  • Prompt-Based Creation: Use a role-specific AI; paste docs for accuracy. Test tools immediately in the UI.

Agents support Model Context Protocol (MCP) compatibility, started by Claude, for seamless integrations (e.g., import Gmail, GitHub, Slack via Composio). You can also expose your agents/tools as MCP servers for use in Cursor or Claude.

Advanced workflows include multi-agent collaboration (e.g., one agent spots arbitrage, another executes), persistent memory for long-term tasks, and in-depth tracing to debug tool calls.

For monetization, share agents in the AI AppStore: Set fees in stablecoins or KAI (with discounts for KAI, e.g., 10% off). This ties into Shinkai's "network of networks," where agents connect across ecosystems for composable services.

Visualizing an advanced agent-tool interaction:

Why This Powers Shinkai's Future

Agent creation makes AI accessible yet powerful, blending local privacy with decentralized scalability. For token holders, it drives adoption through user-generated value; for exchanges, it enables secure, crypto-integrated agents. As of July 14, 2025, v1 sees thousands building agents like learning tutors or running coaches. Future enhancements (subject to risks) include more protocols and AI-driven optimizations. Audited for security, it's built for real utility.

Explore tutorials in our docs or try it on GitHub—whether you're a beginner or building enterprise solutions.