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b17a57b
Initial draft for revising getting started
remotesynth 6ea3ae4
Update quickstart.mdx
remotesynth 71369d6
Clean up the ordering
remotesynth c778969
Clean up CI-CD landing page
remotesynth 9ed0787
Improvements to the AI page
remotesynth 0b1b0dd
Minor improvement to the AI page
remotesynth b08fba1
Merge branch 'main' into revise-getting-started
remotesynth b73231c
Some reworking of the intro and removal of outdated content
remotesynth 72d35ca
Added kubernetes as a secondary path
remotesynth bb1cc26
Modify to note lstk for CI
remotesynth 6ef84e4
Update and rename quickstart.mdx to local-development.mdx
quetzalliwrites b7ebb19
Draft 2: rewrite index.mdx
quetzalliwrites fb4ec71
Delete dead code: src/components/SecondaryPathCard.tsx
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Draft 2: installation.mdx
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Draft 2: local-development.mdx
quetzalliwrites 9ebdb73
Draft 2: Rewrite ci-cd.mdx
quetzalliwrites 4ca4a39
Draft 2: rewrite ai-workflows.mdx
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Draft 2: rewrite auth-token.mdx
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Add Troubleshooting section to auth-token.mdx
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remove dead code from global.css
quetzalliwrites 51aa017
add install options + fix missing closing </LinkButton> tags
quetzalliwrites f17c2b9
update anchor links
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update more anchor links
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fix broken command block
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Apply suggestions from code review
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Update local development getting started guide
HarshCasper 35469fc
Update installation getting started guide
HarshCasper b5a040b
Update auth token getting started guide
HarshCasper 0475773
Update AI workflows getting started guide
HarshCasper 72e8356
Update CI getting started guide
HarshCasper 96a03c6
Fix getting started sidebar order
HarshCasper 75b4bbd
Update getting started onboarding
HarshCasper 54f0ca8
Add getting started FAQ card
HarshCasper bd4cc99
Merge main into getting started branch
HarshCasper b715181
simplify getting started
HarshCasper 2bb60a2
Fix quickstart redirects
HarshCasper c1c86b5
Fix getting started next steps
HarshCasper f7541a7
some minor changes
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fix macos installation commands
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,92 @@ | ||
| --- | ||
| title: AI & Agent Workflows | ||
| description: Use LocalStack with AI coding assistants, MCP clients, and agent-driven infrastructure workflows. | ||
| template: doc | ||
| sidebar: | ||
| order: 6 | ||
| --- | ||
|
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| ## Introduction | ||
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| LocalStack gives AI coding assistants a local AWS-compatible environment to work against. Instead of letting an agent experiment in a real AWS account, you can ask it to create infrastructure, deploy code, inspect logs, and test resources in LocalStack first. | ||
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| This is useful when you want to: | ||
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| - Prototype AWS applications & infrastructure code from natural language prompts. | ||
| - Validate AI-generated Terraform, CDK, or AWS CLI commands before using a cloud account. | ||
| - Give an AI assistant a safe place to inspect resources, debug logs, and iterate on deployments. | ||
| - Use reusable agent instructions for LocalStack-aware infrastructure workflows. | ||
|
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| ## Common workflows | ||
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| There are three common ways to use LocalStack in AI-assisted development: | ||
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| - Use the [LocalStack MCP Server](/aws/tooling/mcp-server/) when your AI assistant supports MCP clients such as Cursor, Claude, Codex, or OpenCode. | ||
| - Use [LocalStack Skills](https://github.com/localstack/skills) when you want reusable agent instructions for deploying and testing AWS architectures against LocalStack. | ||
| - Use LocalStack with `tflocal`, `cdklocal`, or `awslocal` when you want the agent to generate infrastructure code or commands that you review and run locally. | ||
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| You do not need all three approaches to get started. If your editor supports MCP, start with the LocalStack MCP Server. Or, you can use Skills if you want reusable agent instructions. If not, ask your assistant to generate Terraform, CDK, or AWS CLI steps and run them with LocalStack's local wrappers. | ||
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| ## Connect an MCP client | ||
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| The LocalStack MCP Server connects MCP-compatible clients to your LocalStack environment. Once configured, your AI assistant can use LocalStack tools to start the container, deploy infrastructure, run AWS CLI commands, inspect logs, manage state, and query resources. | ||
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| :::note | ||
| The MCP server runs locally and talks to your LocalStack instance. Your AI assistant is the MCP client. For setup instructions and the full tool reference, see the [LocalStack MCP Server guide](/aws/tooling/mcp-server/). | ||
| ::: | ||
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| All MCP server tools require a valid [Auth Token](/aws/getting-started/auth-token/) configured as `LOCALSTACK_AUTH_TOKEN`. | ||
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| ## Use agent skills | ||
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| [LocalStack Skills](https://github.com/localstack/skills) provide reusable instructions for AI agents working with LocalStack. They help agents follow LocalStack-specific conventions when creating infrastructure, deploying resources, running tests, and inspecting local cloud state. | ||
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| Skills are most useful when you want the assistant to follow a repeatable workflow, for example: | ||
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| - Scaffold a local AWS application and deploy it to LocalStack. | ||
| - Convert an AWS architecture idea into Terraform or CDK that targets LocalStack first. | ||
| - Debug a failing local deployment by checking resources, logs, and configuration. | ||
| - Save or restore LocalStack state as part of an iterative development loop. | ||
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| Refer to the [LocalStack Skills repository](https://github.com/localstack/skills) for available skills and setup instructions. | ||
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| ## Example prompt sequence | ||
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| After LocalStack and your preferred AI tooling are configured, you can use a sequence like this: | ||
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| ```text | ||
| Create a Terraform application with an S3 bucket, a Lambda function, and a DynamoDB table. | ||
| Make it deployable to LocalStack with tflocal. | ||
| ``` | ||
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| ```text | ||
| Deploy the application to LocalStack and fix any errors from the deployment. | ||
| ``` | ||
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| ```text | ||
| Invoke the Lambda function locally, inspect the DynamoDB table, and summarize what resources were created. | ||
| ``` | ||
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| ```text | ||
| Add an integration test that verifies the Lambda writes an item to DynamoDB. | ||
| Run the test against LocalStack. | ||
| ``` | ||
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| This keeps the feedback loop local while still giving the assistant a realistic AWS-compatible target. | ||
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| ## Review before applying to AWS | ||
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| AI-generated infrastructure still needs review. Treat LocalStack as the first validation step, not as a replacement for code review, tests, or production deployment controls. | ||
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| Before applying changes to AWS, check that: | ||
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| - The generated infrastructure matches your intended architecture. | ||
| - Resource names, IAM policies, and environment variables are appropriate for your project. | ||
| - Tests pass against LocalStack. | ||
| - You understand any changes the assistant made to application code or deployment configuration. | ||
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| ## Next steps | ||
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| - Configure the [LocalStack MCP Server](/aws/tooling/mcp-server/) if your AI assistant supports MCP. | ||
| - Review [LocalStack Skills](https://github.com/localstack/skills) for reusable agent workflows. | ||
| - Browse the [LocalStack for AWS services](/aws/services/) reference, or check the [Getting Started FAQ](/aws/getting-started/faq/) for common setup questions. | ||
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