derekhu0002/archgraph

Name: derekhu0002/archgraph
Author: derekhu0002

插件Plugin 原生Native ⭐ 2 Apache-2.0 cat_label.agent-frameworkcat_label.agent-framework cat_label.agent-memorycat_label.agent-memory 代理编排Agent Orchestration cat_label.agenticcat_label.agentic cat_label.agentic-aicat_label.agentic-ai cat_label.agentscat_label.agents

An architecture-graph driven framework for Agentic Engineering.

项目介绍Project Overview

由知微Agent(zhiwei)编辑Edited by Zhiwei Agent (zhiwei)

ArchGraph 是架构图驱动的 Agentic Engineering 框架，用 ArchiMate 3.2 意图架构图统一 harness 与产品设计。核心能力是通过 argo-deploy 向 Copilot、Cursor、DSH 等部署 ARGO MCP、技能、规则与代理，使代理先定位架构元素、按测试优先执行并将提交追溯到图。适用于需要多编码代理协同与架构可追溯的项目。注意：语义 Graph RAG 查询需另行配置 Neo4j 和向量引擎。

ArchGraph is an architecture-graph-driven framework for Agentic Engineering. It unifies harness design and target product design in an ArchiMate 3.2 intent architecture graph. Its core capability deploys the ARGO MCP server, skills, rules, and agents to Copilot, Cursor, DeepSeek Harness, and other harnesses via argo-deploy; agents locate architecture elements, work test-first, and trace commits to the graph. Use it for multi-agent coding with architecture traceability. Semantic Graph RAG requires separately configured Neo4j and a vector engine.

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READMEREADME

2.5 KB · 缓存于 2026-08-27 05:41:41 · 2.5 KB

ArchGraph

An architecture-graph driven framework for Agentic Engineering.

What is this?

ArchGraph builds a unified language that puts harness design and target product design into one model — so you get a single view to work and observe, and real control over your agents.

alt text

Architecture

The global architecture (Layered Viewpoint) shows how the human, the coding agent, ARGO MCP, the intent architecture graph, ArchiMate 3.2, and Enterprise Architect relate in graph-driven agentic engineering:

Global architecture — Layered Viewpoint

Editable source: docs/diagrams/global-architecture.excalidraw

Supported Harnesses

ArchGraph deploys the ARGO toolchain to all major coding-agent environments:

Harness	MCP Server	Skills	Rules / Instructions	Agents	Wakeup Gate
GitHub Copilot	✓	✓	✓	✓	—
Cursor	✓	✓	✓	✓	—
OpenCode	✓	✓	✓	✓	✓
DeepSeek Harness	✓	✓	✓	✓	✓
OpenClaw	✓	✓	✓	—	✓

A single argo-deploy registers the argo MCP server and installs all artifacts into each harness automatically.

Install

npm install -g archgraph-argo
argo-deploy

Done — the ARGO toolchain, skills, and rules are deployed, and the argo MCP server is registered automatically in GitHub Copilot, Cursor, OpenCode, DeepSeek Harness (dsh), and OpenClaw.

Semantic (Graph RAG) queries also need Neo4j and a vector engine configured in ~/.argo/.env; everything else works out of the box.

How to use

After installing, open your project and start a coding agent. It will:

locate the architecture element behind the task before changing anything,
arm itself with that element's Skills and Rules,
work test-first (GIVEN-WHEN-THEN), and trace every commit back to the graph.

The intent architecture graph — modelled in ArchiMate 3.2 — is the single source of truth.

License

Apache License 2.0

渲染基于仓库 derekhu0002/archgraph 的 README.md。在 GitHub 查看原文 →

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