# TAG: Terminal AI Agent Orchestration Tool with Multi-Provider Routing and Swarm Cluster Topology

> TAG is a terminal AI agent orchestration tool built on the Hermes runtime. It supports features like multi-provider routing, native kanban layer, background task queue, and Swarm cluster topology, providing developers with full AI workflow management capabilities from task submission to cluster coordination.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-06-15T09:47:44.000Z
- 最近活动: 2026-06-15T09:52:10.467Z
- 热度: 163.9
- 关键词: AI智能体, 终端工具, 多Provider路由, Swarm集群, 任务队列, 看板管理, Hermes, OpenRouter, 智能体编排, CLI工具
- 页面链接: https://www.zingnex.cn/en/forum/thread/tag-ai-providerswarm
- Canonical: https://www.zingnex.cn/forum/thread/tag-ai-providerswarm
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: TAG: Terminal AI Agent Orchestration Tool with Multi-Provider Routing and Swarm Cluster Topology

TAG is a terminal AI agent orchestration tool built on the Hermes runtime. It supports features like multi-provider routing, native kanban layer, background task queue, and Swarm cluster topology, providing developers with full AI workflow management capabilities from task submission to cluster coordination.

## Original Author and Source

- **Original Author/Maintainer**: sanskarpan
- **Source Platform**: GitHub
- **Original Title**: TAG agent: Hermes-based orchestration, packaged runtime, TUI skinning, OpenRouter routing, and Codex-aware workflows
- **Original Link**: https://github.com/sanskarpan/tag-agent
- **Publication Date**: June 15, 2026

## Project Background and Positioning

With the rapid development of AI Agent technology, developers' demand for efficient and flexible agent orchestration tools is growing. Traditional AI tools are often limited to a single provider or specific use cases, making it difficult to meet the orchestration needs of complex workflows. The TAG project was born to provide developers with a unified terminal entry point for flexible scheduling of multi-provider AI models and coordinated management of agent clusters.

TAG is built on the Hermes runtime and adopts an architecture design that separates the management plane from the execution plane. This allows some core functions (such as task queue, kanban management, and credential import) to run offline without an API key, significantly improving the tool's usability and security.

## Core Architecture Design

TAG uses a two-layer architecture to effectively decouple management and execution functions:

## Management Plane

Built on SQLite and can run without an API key:
- **Kanban Layer**: Native task creation and monitoring functions
- **Queue Worker**: Background task queue with priority scheduling support
- **Dashboard**: Real-time terminal view based on the Rich library

## Execution Plane

Built on the Hermes gateway and requires an API key:
- **Swarm Topology**: Task fan-out to multiple worker nodes
- **Submission Engine**: Supports both direct connection and kanban execution modes
- **TUI Interface**: Full terminal user interface

This architecture design allows users to perform operations like task queuing, kanban management, and credential import without an active API key, greatly lowering the barrier to use.

## Multi-Provider Routing Capability

TAG supports a wide range of AI model providers, allowing users to flexibly choose based on task characteristics:

- **OpenRouter**: Unified routing for multi-vendor models
- **Codex**: OpenAI code generation model
- **Claude**: Anthropic dialogue model
- **Gemini**: Google multimodal model
- **Mistral**: European open-source model
- **Groq**: High-performance inference service
- **DeepSeek**: Domestic open-source model
- **Any OpenAI-compatible endpoint**: Supports custom access

Each profile can independently configure models, credentials, and routing strategies to achieve refined resource management.

## Credential Import Ecosystem

TAG provides a one-click credential import function, supporting automatic extraction of API keys from more than 10 local AI tools:

| Command | Source Tool |
|---------|-------------|
| `tag import-claude` | Claude Code |
| `tag import-gemini` | Gemini CLI |
| `tag import-codex` | OpenAI Codex CLI |
| `tag import-continue` | Continue.dev |
| `tag import-mistral` | Mistral Vibe CLI |
| `tag import-copilot` | GitHub Copilot |
| `tag import-aider` | Aider |
| `tag import-aws` | Amazon Bedrock |
| `tag import-cursor` | Cursor |

All import operations only write keys to the `.env` file of the local profile, ensuring credentials never leave the user's machine.