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giovanemartins

LocalStack MCP Server

dynamodb_scan

Scan a DynamoDB table in LocalStack to retrieve all items, with optional filter expressions and limits to control output.

Instructions

Scan all items in a DynamoDB table in LocalStack

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of items to return (default: 100)
tableNameYesTable name
filterExpressionNoDynamoDB filter expression
expressionAttributeValuesNoExpression attribute values as JSON string
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the core action and offers no details about return format, pagination behavior, performance costs (full table read), or how the limit parameter influences results. This is a significant omission for a scan operation.

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

Conciseness4/5

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

The description is a single, compact sentence with no filler words. It is efficiently structured and easy to parse, though it sacrifices detail for brevity. It earns a high conciseness score because every word contributes to the core message.

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

Completeness2/5

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

The tool has no output schema and no annotations, so the description must provide the contextual completeness. It fails to mention return values, pagination, or the fact that a scan reads the entire table and may be expensive. Given the medium complexity and the absence of other context, this description is inadequate.

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

Parameters3/5

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

The schema already describes all four parameters with 100% coverage, so the baseline is 3. The description adds no additional parameter semantics, neither clarifying the JSON format for expressionAttributeValues nor hinting at the effect of limit. It neither improves nor degrades the information available.

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

Purpose4/5

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

The description clearly states the action ('Scan all items') and the resource ('DynamoDB table in LocalStack'), making the primary purpose evident. However, it does not explicitly distinguish from sibling tools like dynamodb_query, so it stops short of full differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use scan versus alternatives such as dynamodb_query. It implies a use case for retrieving all items but does not state any exclusions, prerequisites, or comparisons, leaving the agent without clear decision support.

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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