shinkai local ai agents

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Basic Information

Shinkai is an open-source, cross-platform platform for building and deploying autonomous AI agents with a no-code visual builder. The repository provides a monorepo implementation that ships a Tauri-based desktop app (shinkai-desktop) plus shared libraries for messaging, state, UI components and internationalization. It supports multi-agent orchestration so teams of agents can collaborate, share context, and run multi-step workflows. The platform is crypto-native with built-in support for decentralized payments and DeFi interactions and is compatible with the Model Context Protocol (MCP) so agents can interoperate with models like Claude and Cursor. Shinkai can run locally for privacy or connect to cloud models and includes example agents such as trading bots, email assistants, data intelligence agents and DeFi portfolio managers. The repo includes scripts to download required side binaries such as the Shinkai Node and Ollama models.

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App Details

Features
Shinkai"s README highlights a visual no-code agent builder, multi-agent orchestration, crypto-native architecture for autonomous payments, MCP compatibility, and hybrid local/cloud deployment. It provides one-click installation releases, platform binaries and platform requirements. The codebase is organized as an NX monorepo with a Tauri desktop front end built on React and TypeScript plus shared libraries: shinkai-message-ts, shinkai-node-state, shinkai-ui, shinkai-artifacts and shinkai-i18n. The tech stack includes React 18, TypeScript, Tailwind CSS, Radix UI, Zustand for UI state, React Query for server state, Vite and NX for builds, and Vitest for testing. CI/dev scripts automate download of shinkai-node and Ollama, regeneration of model repos and i18n generation. The project also documents build, serve and test commands and offers multi-language support and community resources.
Use Cases
Shinkai lowers the barrier to building autonomous agents by offering a drag-and-drop interface and prebuilt components so non-developers can create specialized agents quickly. Teams can orchestrate multiple agents to automate complex business workflows such as monitoring markets, executing trades, routing emails, scraping and analyzing data, and managing DeFi portfolios. Local-first operation keeps crypto keys and sensitive data under user control while hybrid deployment lets users augment local models with cloud capabilities. MCP support increases interoperability across AI model ecosystems. The monorepo and developer tooling make it straightforward for developers to extend or customize behavior, rebuild model repositories and generate translations. Documentation, a demo, examples and a Discord community provide practical support for adoption and contribution.

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