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 agentmods add skills/friz-zy/ai-capability-registry/aws-apinpx skills add Friz-zy/ai-capability-registry --skill aws-apigit clone --depth 1 https://github.com/Friz-zy/ai-capability-registryWrote 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/friz-zy/ai-capability-registry/aws-api)<a href="https://agentmods.dev/skills/friz-zy/ai-capability-registry/aws-api"><img src="https://agentmods.dev/badge/skills/friz-zy/ai-capability-registry/aws-api.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00019 | $0.00412 |
| Opus 5 | $0.00010 | $0.00206 |
| Sonnet 5 | $0.00004 | $0.00082 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
aws-api-mcp 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 2d 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.
What it actually says
AWS API
Comprehensive AWS API support with command validation and access to all services.
When to use
- Use AWS API only when the task directly involves the relevant service, SaaS product, platform, or technology.
Connection
Docker stdio
{
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e",
"AWS_SECRET_ACCESS_KEY",
"-e",
"AWS_SESSION_TOKEN",
"mcp/aws-api-mcp-server"
]
}
MCP instructions
- Use the MCP tools only for the user-requested service workflow and prefer read-only operations by default.
- Confirm the target account, workspace, project, repository, or dataset before actions that can read private data or mutate remote state.
- This server requires authorization or environment-provided credentials; ask the user before connecting or requesting access.
Docker launch notes
- Launch through Docker stdio with
docker run --rm -i -e AWS_SECRET_ACCESS_KEY -e AWS_SESSION_TOKEN mcp/aws-api-mcp-server. - Confirm required environment variables before launch: AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN.
References
Security policy
- Trust:
reviewed - Default mode:
manual_review - Permission default:
manual_review - Authentication:
Unspecified in source metadata - Warning: Default mode is
manual_review. - Warning: Permission default is
manual_review. - Required posture: Complete manual review before connecting or invoking tools; this generated record does not grant approval.
What ships with it
1 file 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.
- 2d ago First seen · 66 lines · 19 tokens per session scan A db8614eb3bea
aws-api-mcp is a skill published in the GitHub repository Friz-zy/ai-capability-registry (9 stars, last pushed 5d ago), licensed MIT. It adds 19 tokens to every session and 412 once invoked, about $0.0001 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.
Other skills, from other repositories
analyzing-cloud-storage-access-patterns
Use when detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical…
agentcore-investigation
Investigate Bedrock AgentCore runtime sessions via CloudWatch Logs Insights — resolve session/trace IDs, query OTEL spans, filter noise, build timelines. Use when debugging AgentCore agent sessions, tracing tool calls, or analyzing latency.
netlify-deploy
Deploy web projects to Netlify using the Netlify CLI (npx netlify). Use when the user asks to deploy, host, publish, or link a site/repo on Netlify, including preview and production deploys.
hyperpod-version-checker
Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches…
ecspresso
ECS deployment tool - deploy, manage, and troubleshoot ECS services.
securing-aws-lambda-execution-roles
Securing AWS Lambda execution roles by implementing least-privilege IAM policies, applying permission boundaries, restricting resource-based policies, using IAM Access Analyzer to validate permissions, and enforcing role scoping through SCPs.