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AWS MCP Server

AWS MCP Server

by marcelobrake
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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aws_athena_get_query_results

Retrieve query results from AWS Athena after execution completes. Use this tool to fetch data from completed queries for analysis or reporting.

Instructions

Get results of a completed Athena query execution.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query_execution_id": "<query_execution_id>"
    },
    "name": "aws_athena_get_query_results"
  }
}

Input Schema

NameRequiredDescriptionDefault
profileNoAWS profile name from ~/.aws/config (e.g., 'default', 'production')
regionNoAWS region override (e.g., 'us-east-1', 'sa-east-1')
query_execution_idYesQuery execution ID
max_resultsNoMaximum rows to return (default: 1000)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations provided. Description adds crucial behavioral constraint that query must be 'completed', indicating a state prerequisite. Missing disclosure of pagination behavior (despite max_results parameter), result format/columnar structure, and download size limits inherent to Athena result retrieval.

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?

Single 7-word sentence is extremely front-loaded with zero redundancy. However, brevity is excessive given lack of annotations and pagination complexity; one additional sentence for behavioral constraints would improve utility without harming conciseness.

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

Completeness3/5

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

With no output schema and no annotations, description successfully identifies the core operation but leaves significant gaps for a paginated data retrieval tool. Should specify result format (CSV, JSON), pagination token handling, and integration with the sibling status-checking tool to be complete.

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?

Schema has 100% description coverage, fully documenting all four parameters including profile/region overrides and max_results. Description adds no parameter-specific guidance beyond what schema provides, earning baseline score for high-coverage schemas.

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?

Clear verb 'Get' and resource 'results of a completed Athena query execution' specifies exactly what is retrieved. Distinguishes from sibling 'aws_athena_get_query_execution' by specifying 'results' (data rows) versus execution metadata, though explicit comparison is not stated.

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

Usage Guidelines3/5

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

Specifies prerequisite state 'completed' implying this should not be called on running queries. However, lacks explicit workflow guidance (e.g., 'use aws_athena_get_query_execution first to verify completion') and does not mention error behavior if called prematurely.

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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