Agent Toolkit for AWS is a collection of AWS-supported MCP servers, skills, plugins, commands, and hooks that help AI coding agents build, deploy, and manage applications on AWS. It is used by developers working with AWS services through agents such as Claude Code, Codex, Cursor, and Kiro. The catalogue entries are the toolkit's own agent extensions for AWS development and operations.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/aws/agent-toolkit-for-awsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/plugins/aws/agent-toolkit-for-aws/aws-data-analytics)<a href="https://agentmods.dev/plugins/aws/agent-toolkit-for-aws/aws-data-analytics"><img src="https://agentmods.dev/badge/plugins/aws/agent-toolkit-for-aws/aws-data-analytics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/plugins/aws/agent-toolkit-for-aws/aws-data-analytics"><img src="https://agentmods.dev/badge/plugins/aws/agent-toolkit-for-aws/aws-data-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>Grade A, and why
aws-data-analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
{
"author": {
"name": "Amazon Web Services"
},
"description": "Data lake, analytics, search, streaming, ETL, and orchestration workflows with S3 Tables, AWS Glue, Athena, Amazon Redshift, Amazon OpenSearch Service, Amazon MSK, Amazon Managed Service for Apache Flink, and Amazon MWAA. Covers managed Iceberg tables on S3 Tables, ingestion from JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Amazon Redshift, Snowflake, BigQuery, and DynamoDB, AWS Glue Data Catalog inventory and asset discovery, federated Athena queries, vector storage and semantic search on Amazon S3 Vectors, Amazon OpenSearch Service and Serverless (migration from Solr/Elasticsearch, provisioning, vector/semantic/hybrid search, log analytics, trace analytics), Amazon MSK Provisioned with Standard and Express brokers (cluster sizing, performance and consumer lag troubleshooting, topic management, MSK Replicator for disaster recovery and active-active replication, and Streaming Tables delivery to S3 Tables), migrating self-managed Apache Kafka to MSK Express, Apache Flink application development on Amazon Managed Service for Apache Flink, and Amazon MWAA Provisioned and MWAA Serverless (authoring, testing, and debugging DAGs and workflows, and Airflow version upgrades for provisioned environments).",
"homepage": "https://github.com/aws/agent-toolkit-for-aws",
"keywords": [
"aws",
"amazon",
"amazon-web-services",
"iam",
"analytics",
"data-lake",
"lakehouse",
"athena",
"glue",
"aws-glue",
"data-catalog",
"s3",
"s3-tables",
"s3-vectors",
"iceberg",
"apache-iceberg",
"etl",
"redshift",
"redshift-serverless",
"data-warehouse",
"snowflake",
"bigquery",
"rds",
"dynamodb",
"jdbc",
"secrets-manager",
"vector-search",
"semantic-search",
"rag",
"embeddings",
"vector-database",
"aurora",
"opensearch",
"opensearch-serverless",
"amazon-opensearch-servicWhat it installs
The manifest is a name and a version. 16 skills travel with it, and installing the plugin installs all of them — 2,962 tokens a session between them. Each is measured on its own page, and each can be installed alone.
- Skill upgrading-mwaa-environments A 254 tokens
- Skill testing-mwaa-workflow A 188 tokens
- Skill ingesting-into-data-lake A 228 tokens
- Skill connecting-to-data-source A 171 tokens
- Skill creating-data-lake-table A 139 tokens
- Skill debugging-mwaa-workflow A 194 tokens
- Skill developing-applications-on-managed-service-for-apache-flink A 248 tokens
- Skill exploring-data-catalog A 99 tokens
- Skill querying-data-lake A 105 tokens
- Skill storing-and-querying-vectors A 108 tokens
- Skill migrate-to-msk A 215 tokens
- Skill redshift-guide A 258 tokens
- Skill authoring-mwaa-workflow A 196 tokens
- Skill managing-amazon-msk A 232 tokens
- Skill amazon-opensearch-service A 211 tokens
- Skill finding-data-lake-assets B 116 tokens
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago Changed · +13 lines 299ad0c2ca48
- 21d ago Changed · +6 lines afa0c2cb3f7c
- 1mo ago First seen · 55 lines scan A 9e1e9a318b82
aws-data-analytics is a plugin published in the GitHub repository aws/agent-toolkit-for-aws (2,927 stars, last pushed today), licensed Apache-2.0. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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