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FOR AI AGENTS

Infrastructure your AI agent already knows how to use.

CLI-first. SSH-based. JSON by default. Every rdc command is designed for autonomous agents — no GUI, no browser automation, no custom integrations needed.

$ rdc machine status prod-1 -o json
SSH connection established .... done
Querying renet daemon ......... done
12 repositories, 47 containers .. all healthy
✓ {"success": true, "command": "machine info", "data": {...}}
Format: JSON    Latency: 142ms    Auth: SSH    Tokens: ~200

Illustrative output; actual runs may include extra logs. CLI reference: rdc machine

100%
CLI-native operations
~200
Avg. tokens per response
0
Browser automation needed
THE PROBLEM

AI agents are powerful — but most infrastructure fights them

Your AI coding assistant can write, test, and debug code autonomously. But when it needs to deploy, check status, or manage infrastructure, it hits a wall: GUI-only dashboards, OAuth browser flows, unstable APIs, and responses that blow the context window.

73% of developers plan to use AI agents for infrastructure tasks by 2026 GitHub 2025 [1]
4x more context window used by unstructured vs. JSON output Industry analysis [2]
0% of traditional infrastructure platforms designed for AI agents Market survey [3]
Traditional infrastructure
Step 1 Open dashboard
Step 2 OAuth login
Step 3 Parse HTML
Step 4 Custom API
Step 5 Agent fails
With Rediacc
rdc repo up
JSON
Done
HOW IT WORKS

Three steps to agent-managed infrastructure

1

Configure

Drop an AGENTS.md template into your project root. Your AI assistant reads it on startup and knows every rdc command.

2

Discover

Run rdc agent capabilities to get a structured JSON command tree. The agent knows what's available without documentation.

3

Operate

Deploy, monitor, rollback — all through CLI commands with JSON output. No GUI, no browser, no custom integration.

AI Agent Running
claude-code CLI
rdc repo up SSH
json-output stdout
agent-caps API
rdc
SSH + JSON
Infrastructure Managed
prod-1 12 repos
staging 8 repos
backups snapshots
monitoring health
AGENT-NATIVE DESIGN

Why rdc is built for AI agents

Every design decision in Rediacc prioritizes machine-readable interfaces. Non-TTY detection auto-switches to JSON. The consistent envelope format means agents parse every response the same way. SSH-based auth means no OAuth flows or token management.

Traditional platforms
Rediacc (rdc CLI)
GUI dashboards: requires browser automation or screenshots
CLI-first: every operation is a shell command
OAuth/browser login: agents can't authenticate
SSH keys: agents authenticate like any CLI tool
HTML/unstructured output: 4x token usage, fragile parsing
JSON envelope: consistent schema, ~200 tokens per response
No discovery: agents need docs or hardcoded API calls
rdc agent capabilities: structured command tree at runtime
WHY IT MATTERS

Built for autonomous infrastructure management

Zero integration effort

Drop AGENTS.md in your project. Your AI assistant immediately knows every available command, flag, and workflow.

Context-window friendly

JSON responses average ~200 tokens. The --fields flag lets agents request only the data they need. No wasted context.

Safe by default

--dry-run previews destructive operations. --yes enables automation. Agents can deploy confidently with built-in guardrails.

A message for you

Let your AI agent manage your infrastructure

Install the CLI. Add the AGENTS.md template. Your AI assistant handles the rest.

Get Started Free
$ curl -fsSL https://www.rediacc.com/install.sh | bash