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AgenticGoKit Organization

Welcome to the AgenticGoKit organization — the home of Go-native tools and frameworks for building high-performance, production-grade multi-agent AI systems with complete lifecycle management.


What is AgenticGoKit?

AgenticGoKit is a comprehensive Go ecosystem for building multi-agent AI systems that combine intelligent agents, memory systems, and dynamic tool integrations — all optimized for speed, reliability, and production deployment.

It's designed for developers who want the efficiency of Go, the flexibility of modern AI orchestration, and the robustness required for enterprise-scale systems — from development to deployment.


Vision: Complete AI Lifecycle Management

The AgenticGoKit organization provides an end-to-end solution for agentic AI development:

BuildManageDeployScale

  • AI Framework — Core multi-agent orchestration with memory, RAG, and tool integration
  • Development Tools — CLI scaffolding, templates, and workflow builders
  • Lifecycle Management — Configuration, monitoring, and operational tooling
  • Distribution & Deployment — Single-binary packaging and production-ready infrastructure

We believe AI orchestration should be fast, reliable, and type-safe — with professional tooling for the entire development lifecycle.


The AgenticGoKit Ecosystem

Project Description
AgenticGoKit Core framework for building multi-agent systems in Go.
agk Command-line toolkit for building, scaffolding, and tracing AI agents and workflows.
agk-templates Official template registry for agent workflows, integrations, and production patterns.
agentic-examples Example agent workflows, demos, and production-ready templates.
(Coming Soon) agk-studio Low-code/no-code platform for developing agentic workflows.

New repositories will be added as the ecosystem expands.


Why AgenticGoKit?

For Developers

  • Type Safety — Compile-time checks prevent runtime surprises
  • Native Concurrency — Goroutines enable true parallel execution
  • Single Binary Deployments — No Python dependency issues
  • Production Ready — Error handling, retry logic, observability hooks
  • Template-Driven — Rapid scaffolding with vetted patterns from agk-templates

For AI Systems

  • Multi-Agent Focus — Orchestrate agents collaboratively or sequentially
  • Memory & RAG — Built-in vector databases and retrieval capabilities
  • Dynamic Tooling — MCP protocol support for runtime tool discovery
  • Configuration-Driven — TOML-based, environment-friendly setup
  • Full Lifecycle Support — From prototype to production with integrated tooling

What You Can Build

  • Research Assistants – Multi-agent research pipelines with search and synthesis
  • Conversational Systems – Chat agents with persistent memory and context awareness
  • Data Processing Pipelines – Sequential or collaborative workflows with monitoring and error handling
  • Knowledge Bases – RAG-powered Q&A systems using document ingestion and vector search
  • Custom Integrations – Use agk-templates to bootstrap domain-specific agents rapidly

Complete Lifecycle

┌─────────────┐      ┌──────────────┐      ┌─────────────┐      ┌──────────────┐
│   Develop   │  →   │   Configure  │  →   │   Deploy    │  →   │   Monitor    │
│             │      │              │      │             │      │              │
│ • agk init  │      │ • TOML files │      │ • Binary    │      │ • Tracing    │
│ • Templates │      │ • Env vars   │      │ • Container │      │ • Metrics    │
│ • Framework │      │ • Validation │      │ • K8s ready │      │ • Debugging  │
└─────────────┘      └──────────────┘      └─────────────┘      └──────────────┘

Get Involved

We welcome contributions and ideas from the community:


Links


Built for performance. Designed for production. Powered by Go.

From prototype to production — one framework, complete lifecycle.

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  1. AgenticGoKit AgenticGoKit Public

    Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grad…

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Repositories

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