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# Archcore
> Archcore is a git-native context layer for AI coding agents, covering spec-driven development and context engineering. Archcore keeps specs, architecture, decisions, rules, and plans as typed markdown documents in a .archcore/ directory inside your repository, and loads them into Claude Code, Cursor, GitHub Copilot, Gemini CLI, Codex CLI, and any MCP-aware agent through MCP tools, session hooks, and slash commands. Local-first: no accounts, no telemetry, no external services.
## Main pages
- [Home](https://archcore.ai/): what Archcore is and how to install the CLI or plugin
- [Plugin](https://archcore.ai/plugin/): /archcore slash commands, skills, and guardrails for Claude Code, Cursor, Codex CLI, and GitHub Copilot CLI
- [CLI](https://archcore.ai/cli/): single cross-platform binary that scaffolds .archcore/, runs a local MCP server, and wires session hooks for 8 AI coding agents
- [How to use](https://archcore.ai/how-to-use/): interactive walkthrough covering install, quick start, and day-to-day use
- [Privacy policy](https://archcore.ai/privacy/): local-first data practices
## Reference
- [Context Engineering for AI Coding Agents](https://archcore.ai/context-engineering/): the five properties of engineered context (explicit, structured, selective, versioned, portable), how it differs from prompt engineering and RAG, and what belongs in project context
- [Spec-Driven Development for AI Coding Agents](https://archcore.ai/spec-driven-development/): what a spec is and is not, EARS and BCP 14 clause form, the idea to PRD to spec to plan track, and how specs stay connected after the merge
- [Project Context for AI Coding Agents](https://archcore.ai/project-context/): what belongs in project context, how it differs from agent memory and retrieval, and the three ways persistence usually fails
- [Why Project Context Belongs in Git](https://archcore.ai/git-native-context/): reviewable, versioned, branch-aware, portable, team-owned, and what the alternative