Atlas Agent Engine Templates

Public starter templates for Atlas Agent Engine. Create a local agent with the agentengine CLI, choose an LLM connection, and run it with agentengine dev up.

Quick Start

Prerequisites:

• The agentengine CLI.
• Docker or another container runtime supported by agentengine dev up.
• An API key from the LLM provider you want to use.

agentengine create --template hello-world-agent --name "My First Agent"
cd my-first-agent/agents/my-first-agent
agentengine dev up

agentengine create configures the selected client and saves its credential as LLM_API_KEY in .env. Review the generated README before starting the agent to customize its model, optional memory, or deployment configuration.

Templates

Template	Use when
hello-world-agent	You want a minimal Python agent with optional memory.
hello-world-agent-ts (templates/hello-world-agent-langgraph-ts/)	You want a minimal TypeScript agent.
insurance-agent	You want a realistic Python agent with policies, claims, and human review.
insurance-agent-ts	You want a TypeScript deep-agent example with subagents and human review.
chatbot-client	You want a Next.js chat client with a human-review queue.

LLM Connections

Choose OpenAI, Anthropic, Google Gemini, OpenRouter, or an Azure preset for OpenAI Chat Completions or Anthropic Messages. Azure setup asks for an endpoint, model or deployment name, and API key. The preset supplies the authentication headers and, for Anthropic Messages, the required version header.

For other integrations, select I'll configure it myself and implement the generated LLM builder before running the agent. Supported presets and standalone templates read LLM_API_KEY; keep credentials in .env or the platform secret store, never in source control.

Coding Agent Skills

The CLI installs project-local coding-agent skills into both .agents/skills/ for Codex and Copilot and .claude/skills/ for Claude Code:

• New project: agentengine create installs them as part of scaffolding.
• Existing agent workspace: run agentengine init in the agent directory. It installs the same skills without re-scaffolding, and works for a single agent, a monorepo root, or --workspace-id.

Both commands are safe to run in sequence: existing skill files are left untouched, so local edits are preserved and nothing is duplicated. That also means an already-installed skill is not updated in place.

The Atlas Agent Engine docs skill retrieves and cites https://www.mongodb.com/docs/agentengine on demand. Before that public site is available, it reports that public documentation is not available yet.

Deploying An Agent

After local testing, register the generated agent with agentengine init. Store the agent credential with agentengine secret set LLM_API_KEY before running agentengine build and agentengine deploy. Interactive deploy also offers to upload the credential from .env.

Memory extraction needs its own provider credential and a Voyage key; follow the generated README's memory setup before enabling it.

CI

The public Template Smoke workflow validates the hello-world-agent template on pull requests and updates to main. It checks that the curated repository has no internal references and compiles the starter source.

License

Use of the Atlas Agent Engine software referenced by these templates is governed by the License Agreement.