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genkit-dart

genkit-dart

github.com/genkit-aiDevelopment17538 installsUpdated today
Repository

About genkit-dart

Genkit Dart is an AI SDK for Dart developers building generation, structured-output, tool, flow, and agent applications. Its CLI adds a local development UI for running flows, tracing executions, trying models, and evaluating outputs.

Key features

  1. 01AI generation and structured outputs
  2. 02Tools, flows, and agents
  3. 03Embedding and streaming support
  4. 04Plugin ecosystem for AI integrations
  5. 05CLI development UI and tracing

Use cases

  1. 01Building AI applications in Dart
  2. 02Defining tools and flows
  3. 03Running and tracing flows locally
  4. 04Evaluating model outputs

MCP support

The genkit_mcp plugin provides Model Context Protocol integration, including Server, Host, and Client capabilities.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/genkit-ai/genkit-dart --skill genkit-dart

After installing, type/genkit-dartin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
genkit.md
genkit_anthropic.md
genkit_chrome.md
genkit_firebase_ai.md
genkit_google_genai.md
genkit_mcp.md
genkit_middleware.md
genkit_openai.md
genkit_shelf.md

Details

From the project README

Genkit Dart

Genkit Dart is an AI SDK for Dart that provides a unified interface for code generation, structured outputs, tools, flows, and AI agents.

Core Features and Usage

If you need help with initializing Genkit (Genkit()), Generation (ai.generate), Tooling (ai.defineTool), Flows (ai.defineFlow), Embeddings (ai.embedMany), streaming, or calling remote flow endpoints, please load the core framework reference: references/genkit.md

Genkit CLI (recommended)

The Genkit CLI provides a local development UI for running Flow, tracing executions, playing with models, and evaluating outputs.

check if the user has it installed: genkit --version

Installation:

curl -sL cli.genkit.dev | bash # Native CLI
# OR
npm install -g genkit-cli # Via npm

Usage: Wrap your run command with genkit start to attach the Genkit developer UI and tracing:

genkit start -- dart run main.dart

Plugin Ecosystem

Genkit relies on a large suite of plugins to perform generative AI actions, interface with external LLMs, or host web servers.

When asked to use any given plugin, always verify usage by referring to its corresponding reference below. You should load the reference when you need to know the specific initialization arguments, tools, models, and usage patterns for the plugin:

Plugin NameReference LinkDescription
genkit_google_genaireferences/genkit_google_genai.mdLoad for Google Gemini plugin interface usage.
genkit_anthropicreferences/genkit_anthropic.mdLoad for Anthropic plugin interface for Claude models.
genkit_openaireferences/genkit_openai.mdLoad for OpenAI plugin interface for GPT models, Groq, and custom compatible endpoints.
genkit_middlewarereferences/genkit_middleware.mdLoad for Tooling for specific agentic behavior: filesystem, skills, and toolApproval interrupts.
genkit_mcpreferences/genkit_mcp.mdLoad for Model Context Protocol integration (Server, Host, and Client capabilities).
genkit_chromereferences/genkit_chrome.mdLoad for Running Gemini Nano locally inside the Chrome browser using the Prompt API.
genkit_shelfreferences/genkit_shelf.mdLoad for Integrating Genkit Flow actions over HTTP using Dart Shelf.
genkit_firebase_aireferences/genkit_firebase_ai.mdLoad for Firebase AI plugin interface (Gemini API via Vertex AI).

External Dependencies

Whenever you define schemas mapping inside of Tools, Flows, and Prompts, you must use the schemantic library. To learn how to use schemantic, ensure you read the schemantic skill for how to implement type safe generated Dart code. This is particularly relevant when you encounter symbols like @Schema(), SchemanticType, or classes with the $ prefix. Genkit Dart uses schemantic for all of its data models so it's a CRITICAL skill to understand for using Genkit Dart.

Best Practices

  • Always check that code cleanly compiles using dart analyze before generating the final response.
  • Always use the Genkit CLI for local development and debugging.

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