Design, build, deploy, test, and debug serverless applications with AWS Lambda. Triggers on phrases like: Lambda function, event source, serverless application, API Gateway, EventBridge, Step Functions, serverless API, event-driven architecture, Lambda trigger. For deploying non-serverless apps to AWS, use deploy-on-aws plugin instead.
npx skills add https://github.com/awslabs/agent-plugins --skill aws-lambda
Design, build, deploy, and debug serverless applications with AWS serverless services. This skill provides access to serverless development guidance through the AWS Serverless MCP Server, helping you to build production-ready serverless applications with best practices built-in.
Use SAM CLI for project initialization and deployment, Lambda Web Adapter for web applications, or Event Source Mappings for event-driven architectures. AWS handles infrastructure provisioning, scaling, and monitoring automatically.
Key capabilities:
Load the appropriate reference file based on what the user is working on:
sam_init or cdk init with an appropriate template for your use caseGlobals in SAM, construct props in CDK)secure_esm_* tools to generate correct IAM policies for event source mappings*) resource ARNs or actions in IAM policiesFor topic-specific best practices, see the dedicated guide files in the reference table above.
Limits that developers commonly hit:
| Resource | Limit |
| -------------------------------------------- | ----------------------------------- |
| Function timeout | 900 seconds (15 minutes) |
| Memory | 128 MB – 10,240 MB |
| 1 vCPU equivalent | 1,769 MB memory |
| Synchronous payload (request + response) | 6 MB each |
| Async invocation payload | 1 MB |
| Streamed response | 200 MB |
| Deployment package (.zip, uncompressed) | 250 MB |
| Deployment package (.zip upload, compressed) | 50 MB |
| Container image | 10 GB |
| Layers per function | 5 |
| Environment variables (aggregate) | 4 KB |
| /tmp ephemeral storage | 512 MB – 10,240 MB |
| Account concurrent executions (default) | 1,000 (requestable increase) |
| Burst scaling rate | 1,000 new executions per 10 seconds |
Check Service Quotas for your account limits: aws lambda get-account-settings
| Error | Cause | Solution |
| ----------------------------------- | ------------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------- |
| Build Failed | Missing dependencies | Run sam_build with use_container: true |
| Stack is in ROLLBACK_COMPLETE | Previous deploy failed | Delete stack with aws cloudformation delete-stack, redeploy |
| IteratorAge increasing | Stream consumer falling behind | Increase ParallelizationFactor and BatchSize. Use esm_optimize |
| EventBridge events silently dropped | No DLQ, retries exhausted | Add RetryPolicy + DeadLetterConfig to rule target |
| Step Functions failing silently | No retry on Task state | Add Retry with Lambda.ServiceException, Lambda.AWSLambdaException |
| Durable Function not resuming | Missing IAM permissions | Add lambda:CheckpointDurableExecution and lambda:GetDurableExecutionState — see durable-functions skill |
For detailed troubleshooting, see references/troubleshooting.md.
This skill requires that AWS credentials are configured on the host machine:
Verify access: Run aws sts get-caller-identity to confirm credentials are valid
sam --versionsam_local_invoke and container-based buildsdocker --version or finch --versionWrite access is enabled by default. The plugin ships with --allow-write in .mcp.json, so the MCP server can create projects, generate IaC, and deploy on behalf of the user.
Access to sensitive data (like Lambda and API Gateway logs) is not enabled by default. To grant it, add --allow-sensitive-data-access to .mcp.json.
This plugin includes a PostToolUse hook that runs sam validate automatically after any edit to template.yaml or template.yml. If validation fails, the error is returned as a system message so you can fix it immediately. The hook requires SAM CLI and jq to be installed; if either is missing, validation is skipped with a system message. Users can disable it via /hooks.
Verify: Run jq --version
Default: TypeScript
Override syntax:
When not specified, ALWAYS use TypeScript
Default: CDK
Override syntax:
When not specified, ALWAYS use CDK
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Take awslabs/aws-lambda from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.