Agents Get StartedSAFE

Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: agents-get-started
description: >
  Use when a developer wants to create a new agent project or get started
  with AgentCore. Handles framework selection, project scaffolding, first
  deploy, and first invocation. Triggers on: "build an agent", "create an
  agent", "get started", "new project", "agentcore create", "which
  framework", "Strands vs LangGraph", "hello world agent", "first agent",
  "create MCP server", "host MCP server", "agentcore dev", "dev server",
  "what port", "local development".
  Not for adding capabilities to existing projects — use agents-build
  or agents-connect. Strands vs LangGraph in a migration context routes
  to agents-build, not here. Connecting to an existing MCP server routes
  to agents-connect, not here.
allowed-tools: Read Grep Glob Bash
metadata:
  type: skill
  version: "1.0.0"
  author: aws-agentcore
  requires-cli: ">=0.9.0"
---

# get-started

Walk a developer from zero to a running agent on AWS.

## When to use

- Developer wants to build an agent on AWS and doesn't know where to start
- Developer wants to create a new AgentCore project
- Developer is choosing between frameworks (Strands, LangGraph, GoogleADK, OpenAI Agents)
- Developer just ran `agentcore create` and wants to know what to do next

Do NOT use for:

- Environment/prerequisite issues (CLI not found, credentials broken) → use `agents-debug`
- Adding capabilities to an existing project (memory, tools, policies) → use `agents-build` or `agents-connect`
- Migrating an existing Bedrock Agent → use `agents-build` (loads [`references/migrate.md`](../agents-build/references/migrate.md))

## Input

`$ARGUMENTS` can be:

- A framework preference: "using LangGraph", "with Strands"
- A protocol: "MCP server", "A2A"
- A description of what the agent should do: "a customer support agent"
- Empty — the skill will guide framework selection

## Process

### Step 0: Verify CLI version

```bash
agentcore --version
```

This skill requires v0.9.0 or later.

If the version is older:
> Your AgentCore CLI is out of date (found vX.Y.Z, need v0.9.0+).

Offer to run the update: `agentcore update`. After the update completes, re-check the version to confirm it's ≥0.9.0 before continuing. Preserve any context the developer already provided (framework preference, project name, what they want to build) so they don't have to repeat themselves.

If `agentcore` is not found:
> The AgentCore CLI isn't installed. Run `npm install -g @aws/agentcore` (requires Node.js 20+).
> If you're having trouble with installation, I can run the `agents-debug` skill (which loads [`references/doctor.md`](../agents-debug/references/doctor.md)) to diagnose your environment.

### Step 1: Determine intent — exploring or ready to create?

Before jumping into framework selection, figure out where the developer is:

**Ask the developer:** "Are you exploring options (comparing frameworks, understanding what AgentCore does) or ready to create a project?"

- **Exploring** → Go to Step 2 (framework comparison). Present the options, answer questions, and wait. Do not construct a `create` command until they signal they're ready.
- **Ready to create** → Skip to Step 3 (create the project). If they already specified a framework, skip Step 2 entirely.
- **Already has a project** → Look for `agentcore/agentcore.json` in the current directory. If found, read it and skip to Step 5 (what to do next). Don't re-scaffold.

If the developer's intent is clear from `$ARGUMENTS` (e.g., "create a Strands agent called MyBot"), skip straight to Step 3.

### Step 2: Framework selection

**Check conversation context first.** If the developer already discussed frameworks earlier in this conversation (e.g., from a previous skill invocation), don't re-present the full table. Summarize what was discussed and ask if they've decided, or if anything changed.

If this is the first time discussing frameworks, present the options:

**Supported frameworks (CLI-scaffolded, Python):**

| Framework | CLI value | Best for |
|---|---|---|
| Strands | `Strands` | AWS-native, simplest path, best AgentCore integration |
| LangGraph | `LangChain_LangGraph` | Complex graph-based workflows, existing LangChain investment |
| Google ADK | `GoogleADK` | Teams already using Google's agent toolkit |
| OpenAI Agents | `OpenAIAgents` | Teams already using OpenAI's agent SDK |

**Ask the developer to choose.** Present the options and wait for their selection. Don't assume a default unless they explicitly say they have no preference.

> **Note on naming:** The CLI flag value is the exact string to pass to `--framework`. In prose use the shorter names.

**Default recommendation** (only when the developer says "no preference" or "you pick"): Strands — AWS-native framework with the tightest AgentCore integration and the most samples/docs.

**Key decision points to surface:**

- "Do you have existing agent code in LangGraph or OpenAI Agents?" → use that framework
- "Do you need complex graph-based workflows with conditional branching?" → LangGraph
- "Starting fresh with no preference?" → Strands

#### Framework not listed?

If the developer asks about a framework not in the table above, handle it:

| They ask about | What to say |
|---|---|
| **CrewAI, AutoGen, Semantic Kernel** | Not scaffolded by the CLI, but you can use them via the BYO Container path (below). AgentCore Runtime is framework-agnostic — any code that implements the HTTP contract works. |
| **Anthropic SDK / Claude Agent SDK** | This is a model SDK, not an agent framework. You can use it inside any framework (Strands, LangGraph, etc.) or standalone. For standalone use, wrap it in a container with the Runtime contract. |
| **Claude Code / Cursor / Copilot** | These are IDE tools, not agent frameworks. They're where you *write* agent code, not what you deploy. Pick a framework from the table above for the agent itself. |
| **LangChain (without LangGraph)** | LangChain is a library, LangGraph is the agent framework built

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

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