Welcome to the AgenticGoKit organization — the home of Go-native tools and frameworks for building high-performance, production-grade multi-agent AI systems.
AgenticGoKit is a Go framework 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.
This organization hosts the complete Agentic AI toolkit — a growing collection of Go libraries, SDKs, and utilities for agent-based development.
| Project | Description |
|---|---|
| AgenticGoKit | Core framework for building multi-agent systems in Go. |
| (Coming Soon) agk | Command-line toolkit for building, scaffolding, and managing AI agents and workflows using AgenticGoKit. |
| (Coming Soon) agentic-ai | Opinionated runtime for deploying and scaling agentic applications. |
| (Coming Soon) agentic-tools | Shared connectors, APIs, and tool integrations (MCP, REST, gRPC). |
| (Coming Soon) agentic-examples | Example agent workflows, demos, and production-ready templates. |
New repositories will be added as the ecosystem expands.
| For Developers | For AI Systems |
|---|---|
| Type Safety — Compile-time checks prevent runtime surprises. | Multi-Agent Focus — Orchestrate agents collaboratively or sequentially. |
| Native Concurrency — Goroutines enable true parallel execution. | Memory & RAG — Built-in vector databases and retrieval capabilities. |
| Single Binary Deployments — No Python dependency issues. | Dynamic Tooling — MCP protocol support for runtime tool discovery. |
| Production Ready — Error handling, retry logic, observability hooks. | Configuration-Driven — TOML-based, environment-friendly setup. |
- 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.
The AgenticGoKit organization aims to:
- Provide a complete Go-native stack for building agentic AI systems.
- Encourage open collaboration on performant, production-ready AI infrastructure.
- Bridge the gap between AI research frameworks and real-world deployment.
We believe AI orchestration should be fast, reliable, and type-safe — not tied to heavyweight runtimes.
We welcome contributions and ideas from the community:
- Report issues or suggest features on the core repo.
- Participate in discussions and share your builds (community channels coming soon).
- Contribute code, documentation, or integrations — see our CONTRIBUTING.md.
- Website: https://agenticgokit.com
- Core Repository: AgenticGoKit/AgenticGoKit
- License: Apache 2.0
