ministack-aws-emulator

MiniStack is a free, open-source local AWS emulator (LocalStack replacement) that emulates 25+ AWS services on a single port with no account or license required.

3,823 stars

Best use case

ministack-aws-emulator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

MiniStack is a free, open-source local AWS emulator (LocalStack replacement) that emulates 25+ AWS services on a single port with no account or license required.

Teams using ministack-aws-emulator should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/ministack-aws-emulator/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/adisinghstudent/ministack-aws-emulator/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/ministack-aws-emulator/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How ministack-aws-emulator Compares

Feature / Agentministack-aws-emulatorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

MiniStack is a free, open-source local AWS emulator (LocalStack replacement) that emulates 25+ AWS services on a single port with no account or license required.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# MiniStack AWS Emulator

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.

MiniStack is a free, MIT-licensed drop-in replacement for LocalStack that emulates 25+ AWS services (S3, SQS, DynamoDB, Lambda, SNS, IAM, STS, Kinesis, EventBridge, SecretsManager, SSM, CloudWatch, SES, and more) on a single port (`4566`). No account, no API key, no telemetry. Works with `boto3`, AWS CLI, Terraform, CDK, and any SDK.

---

## Installation

### Option 1: PyPI (simplest)
```bash
pip install ministack
ministack
# Server runs at http://localhost:4566
# Change port: GATEWAY_PORT=5000 ministack
```

### Option 2: Docker Hub
```bash
docker run -p 4566:4566 nahuelnucera/ministack
```

### Option 3: Docker Compose (from source)
```bash
git clone https://github.com/Nahuel990/ministack
cd ministack
docker compose up -d
```

### Verify it's running
```bash
curl http://localhost:4566/_localstack/health
```

---

## Configuration

| Environment Variable | Default | Description |
|---|---|---|
| `GATEWAY_PORT` | `4566` | Port to listen on |
| `S3_PERSIST` | `0` | Set to `1` to persist S3 data to disk |

---

## AWS CLI Usage

```bash
# Set credentials (any non-empty values work)
export AWS_ACCESS_KEY_ID=test
export AWS_SECRET_ACCESS_KEY=test
export AWS_DEFAULT_REGION=us-east-1

# S3
aws --endpoint-url=http://localhost:4566 s3 mb s3://my-bucket
aws --endpoint-url=http://localhost:4566 s3 cp ./file.txt s3://my-bucket/
aws --endpoint-url=http://localhost:4566 s3 ls s3://my-bucket

# SQS
aws --endpoint-url=http://localhost:4566 sqs create-queue --queue-name my-queue
aws --endpoint-url=http://localhost:4566 sqs list-queues

# DynamoDB
aws --endpoint-url=http://localhost:4566 dynamodb list-tables
aws --endpoint-url=http://localhost:4566 dynamodb create-table \
  --table-name Users \
  --attribute-definitions AttributeName=userId,AttributeType=S \
  --key-schema AttributeName=userId,KeyType=HASH \
  --billing-mode PAY_PER_REQUEST

# STS (identity check)
aws --endpoint-url=http://localhost:4566 sts get-caller-identity

# Use a named profile instead
aws configure --profile local
# Enter: test / test / us-east-1 / json
aws --profile local --endpoint-url=http://localhost:4566 s3 ls
```

### awslocal wrapper (from source)
```bash
chmod +x bin/awslocal
./bin/awslocal s3 ls
./bin/awslocal dynamodb list-tables
```

---

## boto3 Usage Patterns

### Universal client factory
```python
import boto3

ENDPOINT = "http://localhost:4566"

def aws_client(service: str):
    return boto3.client(
        service,
        endpoint_url=ENDPOINT,
        aws_access_key_id="test",
        aws_secret_access_key="test",
        region_name="us-east-1",
    )

def aws_resource(service: str):
    return boto3.resource(
        service,
        endpoint_url=ENDPOINT,
        aws_access_key_id="test",
        aws_secret_access_key="test",
        region_name="us-east-1",
    )
```

### S3
```python
s3 = aws_client("s3")

# Create bucket and upload
s3.create_bucket(Bucket="my-bucket")
s3.put_object(Bucket="my-bucket", Key="hello.txt", Body=b"Hello, MiniStack!")

# Download
obj = s3.get_object(Bucket="my-bucket", Key="hello.txt")
print(obj["Body"].read())  # b'Hello, MiniStack!'

# List objects
response = s3.list_objects_v2(Bucket="my-bucket")
for item in response.get("Contents", []):
    print(item["Key"])

# Copy object
s3.copy_object(
    Bucket="my-bucket",
    CopySource={"Bucket": "my-bucket", "Key": "hello.txt"},
    Key="hello-copy.txt",
)

# Enable versioning
s3.put_bucket_versioning(
    Bucket="my-bucket",
    VersioningConfiguration={"Status": "Enabled"},
)

# Presigned URL (works locally)
url = s3.generate_presigned_url(
    "get_object",
    Params={"Bucket": "my-bucket", "Key": "hello.txt"},
    ExpiresIn=3600,
)
```

### SQS
```python
sqs = aws_client("sqs")

# Standard queue
queue = sqs.create_queue(QueueName="my-queue")
queue_url = queue["QueueUrl"]

sqs.send_message(QueueUrl=queue_url, MessageBody='{"event": "user_signup"}')

messages = sqs.receive_message(QueueUrl=queue_url, MaxNumberOfMessages=10)
for msg in messages.get("Messages", []):
    print(msg["Body"])
    sqs.delete_message(QueueUrl=queue_url, ReceiptHandle=msg["ReceiptHandle"])

# FIFO queue
fifo = sqs.create_queue(
    QueueName="my-queue.fifo",
    Attributes={"FifoQueue": "true", "ContentBasedDeduplication": "true"},
)

# Dead-letter queue setup
dlq = sqs.create_queue(QueueName="my-dlq")
dlq_attrs = sqs.get_queue_attributes(
    QueueUrl=dlq["QueueUrl"], AttributeNames=["QueueArn"]
)
sqs.set_queue_attributes(
    QueueUrl=queue_url,
    Attributes={
        "RedrivePolicy": json.dumps({
            "deadLetterTargetArn": dlq_attrs["Attributes"]["QueueArn"],
            "maxReceiveCount": "3",
        })
    },
)
```

### DynamoDB
```python
import json
ddb = aws_client("dynamodb")

# Create table
ddb.create_table(
    TableName="Users",
    KeySchema=[
        {"AttributeName": "userId", "KeyType": "HASH"},
        {"AttributeName": "createdAt", "KeyType": "RANGE"},
    ],
    AttributeDefinitions=[
        {"AttributeName": "userId", "AttributeType": "S"},
        {"AttributeName": "createdAt", "AttributeType": "N"},
    ],
    BillingMode="PAY_PER_REQUEST",
)

# Put / Get / Delete
ddb.put_item(
    TableName="Users",
    Item={
        "userId": {"S": "u1"},
        "createdAt": {"N": "1700000000"},
        "name": {"S": "Alice"},
        "active": {"BOOL": True},
    },
)

item = ddb.get_item(
    TableName="Users",
    Key={"userId": {"S": "u1"}, "createdAt": {"N": "1700000000"}},
)
print(item["Item"]["name"]["S"])  # Alice

# Query
result = ddb.query(
    TableName="Users",
    KeyConditionExpression="userId = :uid",
    ExpressionAttributeValues={":uid": {"S": "u1"}},
)

# Batch write
ddb.batch_write_item(
    RequestItems={
        "Users": [
            {"PutRequest": {"Item": {"userId": {"S": "u2"}, "createdAt": {"N": "1700000001"}, "name": {"S": "Bob"}}}},
        ]
    }
)

# TTL
ddb.update_time_to_live(
    TableName="Users",
    TimeToLiveSpecification={"Enabled": True, "AttributeName": "expiresAt"},
)
```

### SNS + SQS Fanout
```python
sns = aws_client("sns")
sqs = aws_client("sqs")

topic = sns.create_topic(Name="my-topic")
topic_arn = topic["TopicArn"]

queue = sqs.create_queue(QueueName="fan-queue")
queue_attrs = sqs.get_queue_attributes(
    QueueUrl=queue["QueueUrl"], AttributeNames=["QueueArn"]
)
queue_arn = queue_attrs["Attributes"]["QueueArn"]

sns.subscribe(TopicArn=topic_arn, Protocol="sqs", Endpoint=queue_arn)

# Publish — message is fanned out to subscribed SQS queues
sns.publish(TopicArn=topic_arn, Message="hello fanout", Subject="test")
```

### Lambda
```python
import zipfile, io

# Create a zip with handler code
buf = io.BytesIO()
with zipfile.ZipFile(buf, "w") as zf:
    zf.writestr("handler.py", """
def handler(event, context):
    print("event:", event)
    return {"statusCode": 200, "body": "ok"}
""")
buf.seek(0)

lam = aws_client("lambda")

lam.create_function(
    FunctionName="my-function",
    Runtime="python3.12",
    Role="arn:aws:iam::000000000000:role/role",
    Handler="handler.handler",
    Code={"ZipFile": buf.read()},
)

# Invoke synchronously
import json
response = lam.invoke(
    FunctionName="my-function",
    InvocationType="RequestResponse",
    Payload=json.dumps({"key": "value"}),
)
result = json.loads(response["Payload"].read())
print(result)  # {"statusCode": 200, "body": "ok"}

# SQS event source mapping
lam.create_event_source_mapping(
    EventSourceArn=queue_arn,
    FunctionName="my-function",
    BatchSize=10,
    Enabled=True,
)
```

### SecretsManager
```python
sm = aws_client("secretsmanager")

sm.create_secret(Name="db-password", SecretString='{"password":"s3cr3t"}')
secret = sm.get_secret_value(SecretId="db-password")
print(secret["SecretString"])  # {"password":"s3cr3t"}

sm.update_secret(SecretId="db-password", SecretString='{"password":"newpass"}')
sm.delete_secret(SecretId="db-password", ForceDeleteWithoutRecovery=True)
```

### SSM Parameter Store
```python
ssm = aws_client("ssm")

ssm.put_parameter(Name="/app/db/host", Value="localhost", Type="String")
ssm.put_parameter(Name="/app/db/password", Value="secret", Type="SecureString")

param = ssm.get_parameter(Name="/app/db/host")
print(param["Parameter"]["Value"])  # localhost

# Fetch all params under a path
params = ssm.get_parameters_by_path(Path="/app/", Recursive=True)
for p in params["Parameters"]:
    print(p["Name"], p["Value"])
```

### Kinesis
```python
import base64

kin = aws_client("kinesis")

kin.create_stream(StreamName="events", ShardCount=1)
kin.put_record(StreamName="events", Data=b'{"event":"click"}', PartitionKey="user1")

# Get records
shards = kin.list_shards(StreamName="events")
shard_id = shards["Shards"][0]["ShardId"]

iterator = kin.get_shard_iterator(
    StreamName="events",
    ShardId=shard_id,
    ShardIteratorType="TRIM_HORIZON",
)
records = kin.get_records(ShardIterator=iterator["ShardIterator"])
for r in records["Records"]:
    print(base64.b64decode(r["Data"]))
```

### EventBridge
```python
eb = aws_client("events")

# Create a custom bus
eb.create_event_bus(Name="my-bus")

# Put a rule targeting a Lambda
eb.put_rule(
    Name="my-rule",
    EventBusName="my-bus",
    EventPattern='{"source": ["myapp"]}',
    State="ENABLED",
)
eb.put_targets(
    Rule="my-rule",
    EventBusName="my-bus",
    Targets=[{"Id": "1", "Arn": "arn:aws:lambda:us-east-1:000000000000:function:my-function"}],
)

# Emit an event (triggers Lambda target)
eb.put_events(Entries=[{
    "Source": "myapp",
    "DetailType": "UserSignup",
    "Detail": '{"userId": "123"}',
    "EventBusName": "my-bus",
}])
```

### CloudWatch Logs
```python
import time

logs = aws_client("logs")

logs.create_log_group(logGroupName="/app/service")
logs.create_log_stream(logGroupName="/app/service", logStreamName="stream-1")

logs.put_log_events(
    logGroupName="/app/service",
    logStreamName="stream-1",
    logEvents=[
        {"timestamp": int(time.time() * 1000), "message": "App started"},
        {"timestamp": int(time.time() * 1000), "message": "Request received"},
    ],
)

events = logs.get_log_events(
    logGroupName="/app/service",
    logStreamName="stream-1",
)
for e in events["events"]:
    print(e["message"])

# Filter with glob patterns (* and ?), AND terms, -exclusions
filtered = logs.filter_log_events(
    logGroupName="/app/service",
    filterPattern="Request*",
)
```

---

## Testing Patterns

### pytest fixture (recommended)
```python
import pytest
import boto3

MINISTACK_ENDPOINT = "http://localhost:4566"

@pytest.fixture(scope="session")
def aws_endpoint():
    return MINISTACK_ENDPOINT

@pytest.fixture
def s3_client(aws_endpoint):
    return boto3.client(
        "s3",
        endpoint_url=aws_endpoint,
        aws_access_key_id="test",
        aws_secret_access_key="test",
        region_name="us-east-1",
    )

@pytest.fixture
def test_bucket(s3_client):
    bucket = "test-bucket"
    s3_client.create_bucket(Bucket=bucket)
    yield bucket
    # Cleanup
    objs = s3_client.list_objects_v2(Bucket=bucket).get("Contents", [])
    for obj in objs:
        s3_client.delete_object(Bucket=bucket, Key=obj["Key"])
    s3_client.delete_bucket(Bucket=bucket)

def test_upload_download(s3_client, test_bucket):
    s3_client.put_object(Bucket=test_bucket, Key="test.txt", Body=b"hello")
    resp = s3_client.get_object(Bucket=test_bucket, Key="test.txt")
    assert resp["Body"].read() == b"hello"
```

### GitHub Actions CI integration
```yaml
# .github/workflows/test.yml
name: Test

on: [push, pull_request]

jobs:
  test:
    runs-on: ubuntu-latest
    services:
      ministack:
        image: nahuelnucera/ministack
        ports:
          - 4566:4566
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"
      - run: pip install -r requirements.txt
      - run: pytest
        env:
          AWS_ACCESS_KEY_ID: test
          AWS_SECRET_ACCESS_KEY: test
          AWS_DEFAULT_REGION: us-east-1
          AWS_ENDPOINT_URL: http://localhost:4566
```

### Using AWS_ENDPOINT_URL env var (boto3 >= 1.28)
```python
import os
import boto3

# If AWS_ENDPOINT_URL is set, boto3 uses it automatically — no endpoint_url kwarg needed
# export AWS_ENDPOINT_URL=http://localhost:4566
s3 = boto3.client("s3")  # picks up AWS_ENDPOINT_URL automatically
```

---

## Supported Services (25+)

| Service | Key Operations |
|---|---|
| S3 | CRUD, multipart, versioning, encryption, lifecycle, CORS, ACL, notifications |
| SQS | Standard & FIFO queues, DLQ, batch ops |
| SNS | Topics, subscriptions, fanout to SQS/Lambda, platform endpoints |
| DynamoDB | Tables, CRUD, Query, Scan, TTL, transactions, batch ops |
| Lambda | Python runtimes, invoke, SQS event sources, Function URLs |
| IAM | Users, roles, policies, groups, instance profiles, OIDC |
| STS | GetCallerIdentity, AssumeRole, GetSessionToken |
| SecretsManager | Full CRUD, rotation, versioning |
| SSM Parameter Store | String, SecureString, StringList, path queries |
| EventBridge | Buses, rules, targets, Lambda dispatch |
| Kinesis | Streams, shards, records, iterators |
| CloudWatch Metrics | PutMetricData, alarms, dashboards, CBOR protocol |
| CloudWatch Logs | Log groups/streams, filter with globs, metric filters |
| SES | Send email, templates, configuration sets |
| Step Functions | State machine CRUD |
| RDS | Spins up real Postgres/MySQL containers |
| ElastiCache | Spins up real Redis containers |
| Athena | Real SQL via DuckDB |
| ECS | Real Docker containers |

---

## Troubleshooting

**Connection refused on port 4566**
```bash
# Check if ministack is running
curl http://localhost:4566/_localstack/health
# Start it
ministack
# or
docker run -p 4566:4566 nahuelnucera/ministack
```

**`NoCredentialsError` from boto3**
```bash
export AWS_ACCESS_KEY_ID=test
export AWS_SECRET_ACCESS_KEY=test
export AWS_DEFAULT_REGION=us-east-1
# Any non-empty values work — MiniStack doesn't validate credentials
```

**`InvalidSignatureException`**
- This is usually a region mismatch. Ensure `region_name="us-east-1"` matches across all clients.

**Lambda function not found after create**
- MiniStack executes Python runtimes with a warm worker pool. Wait briefly or invoke with `InvocationType="Event"` for async.

**S3 data lost on restart**
```bash
# Enable persistence
S3_PERSIST=1 ministack
# or in Docker
docker run -p 4566:4566 -e S3_PERSIST=1 -v $(pwd)/data:/data nahuelnucera/ministack
```

**Port conflict**
```bash
GATEWAY_PORT=5000 ministack
# Then use http://localhost:5000 as endpoint
```

**Migrating from LocalStack**
- Replace all `http://localhost:4566` endpoint URLs — they stay the same.
- Remove `LOCALSTACK_AUTH_TOKEN` / `LOCALSTACK_API_KEY` env vars (not needed).
- Replace `localstack/localstack` Docker image with `nahuelnucera/ministack`.
- All `boto3` client code works without modification.

Related Skills

---

3891
from openclaw/skills

name: article-factory-wechat

Content & Documentation

humanizer

3891
from openclaw/skills

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Content & Documentation

find-skills

3891
from openclaw/skills

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

General Utilities

tavily-search

3891
from openclaw/skills

Use Tavily API for real-time web search and content extraction. Use when: user needs real-time web search results, research, or current information from the web. Requires Tavily API key.

Data & Research

baidu-search

3891
from openclaw/skills

Search the web using Baidu AI Search Engine (BDSE). Use for live information, documentation, or research topics.

Data & Research

agent-autonomy-kit

3891
from openclaw/skills

Stop waiting for prompts. Keep working.

Workflow & Productivity

Meeting Prep

3891
from openclaw/skills

Never walk into a meeting unprepared again. Your agent researches all attendees before calendar events—pulling LinkedIn profiles, recent company news, mutual connections, and conversation starters. Generates a briefing doc with talking points, icebreakers, and context so you show up informed and confident. Triggered automatically before meetings or on-demand. Configure research depth, advance timing, and output format. Walking into meetings blind is amateur hour—missed connections, generic small talk, zero leverage. Use when setting up meeting intelligence, researching specific attendees, generating pre-meeting briefs, or automating your prep workflow.

Workflow & Productivity

self-improvement

3891
from openclaw/skills

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Agent Intelligence & Learning

botlearn-healthcheck

3891
from openclaw/skills

botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.

DevOps & Infrastructure

linkedin-cli

3891
from openclaw/skills

A bird-like LinkedIn CLI for searching profiles, checking messages, and summarizing your feed using session cookies.

Content & Documentation

notebooklm

3891
from openclaw/skills

Google NotebookLM 非官方 Python API 的 OpenClaw Skill。支持内容生成(播客、视频、幻灯片、测验、思维导图等)、文档管理和研究自动化。当用户需要使用 NotebookLM 生成音频概述、视频、学习材料或管理知识库时触发。

Data & Research

小红书长图文发布 Skill

3891
from openclaw/skills

## 概述

Content & Documentation