ADK-TS

ADK-TS

ADK-TS is a TypeScript-native, production-ready framework for building hierarchical, multi-agent AI systems with built-in tool integration, memory services, and real-time streaming.

ADK-TS is ai software teams evaluate for ai agents. Use this page to review pricing, integration signals, and the best alternatives before you commit.

Contact for pricing API 70/100
#524 in AI Agents (524 tools)
Added 1 year ago
Data reviewed Jul 15, 2026

Profile facts come from the vendor source. AiMatch labels unknown pricing or API details instead of estimating them.

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Quick Overview

Best for: AI Agents

What it does

AI software for decision-makers comparing workflow fit and alternatives.

Best fit

AI Agents

Pricing snapshot

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ADK-TS

ADK-TS is a TypeScript-native framework designed to build sophisticated, production-ready AI agents and multi-agent workflows. It provides a fluent AgentBuilder API for rapid agent creation, multi-LLM support (OpenAI, Google Gemini, Anthropic Claude, AI SDK models and more), and enterprise-grade capabilities such as session management, memory services, streaming, and artifact handling. The framework targets developers and organizations building hierarchical, tool-enabled agent systems with TypeScript's type safety and modern developer tooling.

Comprehensive framework for building sophisticated AI agents with multi-LLM support, advanced tool integration, memory systems, and flexible conversation flows.

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Key Features

AgentBuilder API

Fluent interface for rapid agent creation with zero boilerplate; supports one-line agents as well as complex workflows.

Multi-LLM Support

Unified interface to switch between OpenAI, Google Gemini, Anthropic Claude, AI SDK models and more.

Production-ready Components

Built-in session management, memory services, streaming, and artifact handling designed for enterprise deployment.

Advanced Tooling

Support for custom tools, function integration, Google Cloud tools, MCP support, and automatic schema generation.

Multi-Agent Workflows

Orchestrate complex workflows with parallel, sequential, and hierarchical agent architectures.

Developer Experience

TypeScript-first design with IntelliSense-friendly APIs, comprehensive examples, and guided documentation.

Memory Services

Integrate vector memory services into agents for persistent context and retrieval.

Real-time Streaming

Support for streaming responses and real-time agent interactions.

Pricing

Current pricing details are not available from the vendor source.

Use Cases

Conversational Assistants

Build helpful AI assistants with session management, instructions, and tool access (search, HTTP) for real-time user interactions.

Research & Analysis Workflows

Compose multi-agent research pipelines (sequential or parallel) to analyze market trends, aggregate findings, and produce summaries.

Enterprise Automation

Deploy production-ready agent systems with memory, artifact handling, and integration with cloud tools for business workflows.

Tool-Augmented Agents

Create agents that call external tools (GoogleSearchTool, HttpRequestTool, custom tools) and integrate results into agent reasoning.

Integrations

OpenAI / Google Gemini / Anthropic / AI SDK models

Supported LLM providers that can be swapped via the unified interface.

GoogleSearchTool

Example tool for web search integration within agents.

HttpRequestTool

Example tool for making HTTP requests from agents.

Google Cloud tools & MCP

Mentions support for Google Cloud tools and MCP servers for deployment/integration.

Benefits

Type safety and developer ergonomics from a TypeScript-native API
Flexibility to use multiple LLM providers via a unified interface
Production-grade features (sessions, memory, streaming) that accelerate deployment
Scalable multi-agent orchestration for complex workflows
Comprehensive documentation, examples, and examples to speed development

Limitations

No verified limitations are available.

Frequently Asked Questions

No verified FAQs are available.

Getting Started

  1. 1 Install the package: npm install @iqai/adk or equivalent
  2. 2 Choose and configure your LLM provider (OpenAI, Google Gemini, Anthropic, AI SDK models, etc.)
  3. 3 Import AgentBuilder, create an agent or workflow, add tools and memory, then call .ask() or .build() to run

Support

docs

Comprehensive documentation, guides, API Reference, CLI Reference and examples available on the site.

issues

Issues & Support (repository or tracking) referenced in site navigation for reporting bugs or requesting help.

community

Community discussions and contributions links available in site navigation.

newsletter

Site footer includes a newsletter sign-up option.

API

Available: Yes
Documentation:

https://adk.iqai.com/

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