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AWS MCP Server

AWS MCP Server

by marcelobrake
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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aws_athena_get_query_execution

Retrieve status and detailed results for an AWS Athena query execution using the query execution ID.

Instructions

Get status and details of an 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_execution"
  }
}

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. 'Get status' implies a safe read operation without side effects, which is valuable behavioral context. However, it lacks specifics on what status values are returned (e.g., QUEUED, RUNNING, SUCCEEDED, FAILED), polling expectations, or AWS permission requirements.

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 sentence of nine words with no filler. Information density is high: verb ('Get'), target ('status and details'), and scope ('Athena query execution') are all present. However, extreme brevity leaves no room for necessary context like lifecycle relationships.

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?

Without annotations or output schema, and given this is part of a multi-step Athena workflow (start → check status → get results), the description is minimally viable but incomplete. It should reference the query lifecycle relationship to aws_athena_start_query_execution and indicate that execution must be SUCCEEDED before calling aws_athena_get_query_results.

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 coverage is 100%, so the schema fully documents all three parameters (profile, region, query_execution_id). The description mentions 'query execution' which aligns with the required query_execution_id parameter but adds no semantic context for the optional AWS profile/region overrides or their syntax beyond what the schema provides.

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 verb 'Get' and resource 'Athena query execution' with specific scope 'status and details'. However, it fails to distinguish from sibling aws_athena_get_query_results, which also operates on query executions but returns result data rather than metadata/status.

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?

No guidance provided on when to use this tool versus alternatives. Given the presence of aws_athena_start_query_execution and aws_athena_get_query_results siblings, the description should clarify this is for polling query state after starting a query and before retrieving results.

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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