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@yawlabs/aws-mcp

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by YawLabs

aws_call

Run any AWS API operation by specifying the service and operation in kebab-case, with parameters as a JSON object. Returns parsed JSON output.

Instructions

Run an arbitrary AWS API operation via the aws CLI. Use kebab-case service and operation names as in aws help (service='s3api', operation='list-buckets'). Pass params as a JSON object using the AWS API's PascalCase keys (e.g. {Bucket: 'foo'}); they go through --cli-input-json. Session profile/region (from aws_session_set) are used by default; override per-call when needed. For high-level wrappers like 'aws s3 cp' or 'aws ec2 wait', use your shell — this tool targets the low-level API. Returns parsed JSON output by default, plus the literal command that was run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceYesAWS service name in kebab-case: 's3api', 'ec2', 'iam', 'lambda', 'dynamodb', 'logs', 'sts', 'cloudformation', etc.
operationYesOperation name in kebab-case: 'list-buckets', 'describe-instances', 'get-caller-identity', 'put-object'.
paramsNoOperation parameters as a JSON object (AWS API schema, PascalCase keys). E.g. {Bucket: 'foo', Key: 'bar'}.
queryNoJMESPath expression to extract a subset of the response (passed as --query). E.g. 'Buckets[].Name', 'Reservations[].Instances[].{Id:InstanceId,State:State.Name}'. Dramatically reduces output size; reach for this whenever you only need a few fields.
profileNoOverride session profile for this call.
regionNoOverride session region for this call.
outputFormatNoOutput format. Default 'json' (parsed into structured data when possible).
timeoutMsNoTimeout in milliseconds. Default 60000 (60s). Raise for slow ops; lower to fail fast.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only provide basic hints, but the description adds significant context: params go via --cli-input-json, returns parsed JSON and the raw command, timeout defaults to 60s, and query parameter reduces output. Could still mention error handling or permission requirements, but overall strong.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (4 sentences) and well-structured: main purpose first, then conventions, then usage boundaries, then output details. Every sentence adds value with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 params, no output schema, many siblings), the description covers all essential aspects: what it does, how to call it, parameter formats, when to use vs alternatives, and return behavior. It is fully sufficient for correct agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All 8 parameters have schema descriptions (100% coverage), and the description adds meaningful extra context: kebab-case naming, PascalCase keys for params, JMESPath usage for query, and advice to use query for smaller output. This goes well beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Run an arbitrary AWS API operation via the aws CLI.' It specifies the naming convention (kebab-case) and distinguishes from high-level wrappers, making its purpose unambiguous and distinct from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use this tool (for low-level API operations) and when not to (use shell for high-level wrappers like 'aws s3 cp'). It also mentions session defaults and per-call overrides, providing clear guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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