Cargo Ai

Wraps the Cargo CLI for managing AI agent resources: creating agents, configuring releases (system prompts, models, temperature), attaching knowledge for RAG, connecting MCP servers, and managing agent memories. Uses a draft-then-deploy workflow where you edit a draft release and explicitly deploy it to make changes live. Notably missing CLI flags for structured output (JSON Schema) and heartbeat configuration, even though the underlying API supports them. You'll need direct API calls for those. Good separation of concerns: this handles agent setup and configuration, while cargo-content manages knowledge files and cargo-orchestration handles actually sending messages to agents.

skills.sh installs: 11.2K
GitHub stars: 22
last updated: Aug 21, 2026

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Install

$ npx -y skills add getcargohq/cargo-skills --skill cargo-ai --agent claude-code

Installs into .claude/skills of the current project.

Files

Cargo CLI — AI

Agent resource management: creating and configuring agents, attaching knowledge for retrieval-augmented generation (RAG), connecting MCP servers, and managing agent memories.

For using agents (sending messages, multi-turn chat, polling), use cargo-orchestration. For uploading knowledge files and building knowledge libraries (the content domain), use cargo-content. This skill covers how that knowledge attaches to an agent. For workspace administration — folders (used to organize agents and files), users, API tokens, roles, and submitting reports when the CLI fails — use cargo-workspace-management.

See references/response-shapes.md for full JSON response structures. See references/troubleshooting.md for common errors and how to fix them. See references/examples/agents.md for agent CRUD and configuration examples. See references/examples/mcp-servers.md for MCP server creation and management examples.