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.
npx skills add aws/agent-toolkit-for-aws --skill storing-and-querying-vectorsgit 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/skills/aws/agent-toolkit-for-aws/storing-and-querying-vectors)<a href="https://agentmods.dev/skills/aws/agent-toolkit-for-aws/storing-and-querying-vectors"><img src="https://agentmods.dev/badge/skills/aws/agent-toolkit-for-aws/storing-and-querying-vectors/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/skills/aws/agent-toolkit-for-aws/storing-and-querying-vectors"><img src="https://agentmods.dev/badge/skills/aws/agent-toolkit-for-aws/storing-and-querying-vectors.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00108 | $0.01892 |
| Opus 5 | $0.00054 | $0.00946 |
| Sonnet 5 | $0.00022 | $0.00378 |
| Haiku 4.5 | $0.00011 | $0.00189 |
Grade A, and why
storing-and-querying-vectors 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 7d 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Store and Query Vectors with Amazon S3 Vectors
Overview
Amazon S3 Vectors is a cost-effective AWS service for storing and querying vector embeddings at scale. Optimized for long-term storage with subsecond latency for cold queries, as low as 100ms for warm queries.
Decision Guide
- Hundreds/thousands of sustained queries per second (QPS): Wrong tool. Recommend OpenSearch.
- Hybrid search, aggregations, faceted search: Recommend OpenSearch with S3 Vectors as storage engine. For OpenSearch integration, search AWS docs for
"Using S3 Vectors with OpenSearch Service". - Tiered (bulk + hot): S3 Vectors for storage + OpenSearch Serverless for real-time. See
references/limits-and-patterns.md. - Cost-effective storage, infrequent queries, RAG: S3 Vectors is the right fit. Proceed.
For latest guidance, search AWS docs for "S3 Vectors best practices".
Common Tasks
Classify the request before starting:
- Simple query: Existing index, skip to Step 6
- Standard: You MUST list existing indexes first and suggest reusing if relevant. Else, new index + store vectors, follow Steps 2-6
- Migration or multi-tenant: Read
references/limits-and-patterns.mdfirst, then Steps 2-6
You MUST execute commands using AWS MCP server tools when connected. Fall back to AWS CLI only if AWS MCP is unavailable. You MUST explain each step to the user before executing.
1. Verify Dependencies
Constraints:
- You MUST check whether AWS MCP tools or AWS CLI is available and inform user if missing
- You MUST confirm target AWS region
2. Create a Vector Bucket
You MUST confirm bucket name with user. Names: 3-63 chars, lowercase letters, numbers, hyphens only. Encryption (SSE-S3 default or SSE-KMS for compliance) is immutable after creation.
aws s3vectors create-vector-bucket \
--vector-bucket-name <BUCKET_NAME>
Constraints:
- You MUST explain encryption cannot be changed after creation
- For SSE-KMS, KMS key policy MUST grant
kms:GenerateDataKeyandkms:Decryptto the S3 Vectors service principalindexing.s3vectors.amazonaws.com. You MUST use full KMS key ARN (not alias). Seereferences/limits-and-patterns.mdfor command example.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 162 lines · 108 tokens per session scan A c7b2d0947ba0
storing-and-querying-vectors is a skill published in the GitHub repository aws/agent-toolkit-for-aws (2,579 stars, last pushed today), licensed Apache-2.0. It adds 108 tokens to every session and 1,892 once invoked, about $0.0005 per session on Opus 5. 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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