System Context Platform — keeps humans and AI in sync with your system.
AI coding agents start every session with amnesia. Your architectural decisions, coding standards, past incidents, and project context are scattered across wikis, Slack threads, and tribal knowledge. Each new session means re-explaining the same things.
Archcore fixes this. It creates a .archcore/ directory in your repository — a structured, version-controlled knowledge base that AI agents read automatically:
- 10 document types — ADRs, RFCs, Rules, Guides, Plans, and more — each with purpose-built templates
- Integrates with 8 AI coding agents — Claude Code, Cursor, Gemini CLI, GitHub Copilot, Codex CLI, OpenCode, Roo Code, and Cline
- MCP server for real-time context injection into any LLM-powered tool
- Local-first and Git-friendly — lives in your repo, versioned with your code, shared with your team
- Cloud sync for cross-project knowledge discovery (coming soon)
- Quick Start
- Installation
- How It Works
- Try It
- Commands
- AI Agent Integration
- Configuration
- Development
- Links & License
# Install
curl -fsSL https://archcore.ai/install.sh | bash
# Initialize in your project
cd your-project
archcore init
# Check your setup
archcore doctorcurl -fsSL https://archcore.ai/install.sh | bashgo install github.com/archcore-ai/cli@latestgit clone https://github.com/archcore-ai/cli.git
cd cli
go build -o archcore .Supported platforms: macOS, Linux, Windows — amd64 and arm64.
- Initialize —
archcore initcreates a.archcore/directory and auto-installs MCP server config for your AI coding agent. - Build context — add documents through your AI agent (via MCP tools) or by hand — both work equally well.
- Stay in sync — every agent session starts with your full project context loaded automatically.
.archcore/
├── settings.json
├── .sync-state.json
├── auth/
│ ├── jwt-strategy.adr.md
│ └── auth-redesign.prd.md
├── payments/
│ └── stripe.adr.md
└── infrastructure/
└── migration.plan.md
The directory structure is free-form — organize documents by domain, feature, team, or any structure that fits your project. Categories are virtual, derived from the document type in the filename (slug.type.md).
Archcore CLI is best example for how it works: https://github.com/archcore-ai/cli/tree/main/.archcore
After archcore init, open your AI agent and start talking. The agent already knows your existing documents and has tools to create new ones.
"We decided to use PostgreSQL instead of MongoDB for our primary database. Record this decision."
Creates infrastructure/use-postgres.adr.md — Context, Decision, Alternatives Considered, and Consequences filled from your conversation.
"We have a team convention: always wrap errors with context using fmt.Errorf and %w. Make this a rule."
Creates backend/error-wrapping.rule.md with imperative statements, rationale, and good/bad code examples.
"Last week we had a connection pool exhaustion incident because idle connections weren't being recycled. Document this so we don't repeat it."
Creates incidents/connection-pool-exhaustion.cpat.md — root cause analysis and prevention steps.
"I need a PRD for the user notifications feature — push, email digests, and in-app alerts."
Creates notifications/user-notifications.prd.md with goals, user stories, requirements, and success metrics.
"Create an implementation plan for the notifications PRD and link them together."
Creates notifications/notifications-implementation.plan.md with phased tasks, then links it to the PRD with an implements relation.
"Quick idea: what if we added a GraphQL API alongside REST?"
Creates api/graphql-support.idea.md — lightweight capture with value assessment and possible implementation.
Arcor has 3 fundamental layers of knowledge: Vision, Knowledge, Experience.
| Type | Full Name | Category | Description |
|---|---|---|---|
prd |
Product Requirements Document | Vision | Goals, user stories, acceptance criteria, and success metrics |
idea |
Idea | Vision | Lightweight capture of a product or technical idea for future exploration |
plan |
Plan | Vision | Phased task list with acceptance criteria and dependencies |
adr |
Architecture Decision Record | Knowledge | Captures a finalized technical decision with context, alternatives, and consequences |
rfc |
Request for Comments | Knowledge | Proposes a significant change open for team review and feedback |
rule |
Rule | Knowledge | Coding or process standard — imperative statements with good/bad examples |
guide |
Guide | Knowledge | Step-by-step how-to instructions for completing a specific task |
doc |
Document | Knowledge | Reference documentation — lookup tables, registries, descriptive material |
task-type |
Task Type | Experience | Recurring workflow pattern — reusable checklist and workflow for a common task |
cpat |
Code Change Patterns | Experience | Root-cause analysis of a bug or incident with prevention steps |
Each document is a Markdown file with YAML frontmatter:
---
title: "Use PostgreSQL for Primary Storage"
status: draft
---
## Context
...Valid statuses: draft, accepted, rejected for all types of documents.
Documents can be linked with directed relations to other documents:
- related — general association
- implements — source implements what target specifies
- extends — source builds upon target
- depends_on — source requires target to proceed
Relations are stored in .sync-state.json and managed automatically by the AI agent through MCP tools.
| Command | Description |
|---|---|
archcore init |
Initialize .archcore/ directory interactively |
archcore doctor |
Run diagnostic checks on your setup |
archcore validate |
Validate document structure and frontmatter |
archcore config |
View or modify settings |
archcore hooks install |
Install hooks for detected AI agents |
archcore update |
Update archcore to the latest version |
archcore mcp |
Run the MCP stdio server |
archcore mcp install |
Install MCP config for detected agents |
# Update to the latest version
archcore updateThe command checks GitHub Releases for a newer version, downloads it, verifies the SHA-256 checksum, and atomically replaces the current binary.
# Install integrations for a specific agent
archcore hooks install --agent cursor
archcore mcp install --agent gemini-cliArchcore integrates with AI coding agents in two ways:
- Hooks inject context at session start, so the agent is aware of your
.archcore/documents from the first message. - MCP (Model Context Protocol) gives the agent tools to list, read, create, update, and link documents in real time.
| Agent | Hooks | MCP |
|---|---|---|
| Claude Code | yes | yes |
| Cursor | yes | yes |
| Gemini CLI | yes | yes |
| GitHub Copilot | yes | yes |
| OpenCode | — | yes |
| Codex CLI | — | yes |
| Roo Code | — | yes |
| Cline | — | manual |
# Auto-detect agents in your project and install everything
archcore hooks install
# Or target a specific agent
archcore mcp install --agent opencodeSettings are stored in .archcore/settings.json and created during archcore init.
| Field | Description | Values |
|---|---|---|
sync |
Sync mode. Cloud and on-prem coming soon. | none (local only), cloud, on-prem |
language |
Documents language. Helps the agent understand in which language to generate documentation | String, defaults to en |
archcore config # show all settings
archcore config get <key> # get a specific value
archcore config set <key> <value> # set a value- Go 1.24+
# Build
go build -o archcore .
# Run all tests
go test ./...
# Run a specific package
go test ./cmd/
# Run a single test
go test ./cmd/ -run TestConfigCmd├── cmd/ # Cobra commands (init, doctor, config, validate, hooks, mcp, ...)
├── internal/
│ ├── agents/ # 8 supported AI agents with hooks/MCP capabilities
│ ├── api/ # HTTP client for archcore server
│ ├── config/ # Settings management and directory init
│ ├── display/ # Terminal output formatting (lipgloss)
│ ├── update/ # Self-update logic (version check, download, verify, replace)
│ ├── mcp/ # MCP stdio server implementation
│ └── sync/ # Sync logic
├── templates/ # 10 document type templates
├── install.sh # Install script
└── .goreleaser.yaml # Release configuration
- Website: archcore.ai
- Issues: github.com/archcore-ai/cli/issues
- License: Apache 2.0