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AWS MCP Server

AWS MCP Server

by marcelobrake
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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aws_athena_list_databases

Retrieve available databases from an AWS Athena data catalog to identify and access structured data sources for querying and analysis.

Instructions

List databases in an Athena data catalog.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "aws_athena_list_databases"
  }
}

Input Schema

NameRequiredDescriptionDefault
profileNoAWS profile name from ~/.aws/config (e.g., 'default', 'production')
regionNoAWS region override (e.g., 'us-east-1', 'sa-east-1')
catalog_nameNoData catalog name (default: AwsDataCatalog)
max_resultsNoMaximum databases to return

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 but only states the basic action. It does not explain pagination behavior (despite max_results parameter), the default catalog behavior, whether this is a read-only operation, or what the response structure looks like.

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?

Extremely concise at 7 words. The single sentence earns its place by stating the core function directly, though the brevity contributes to gaps in behavioral and contextual information. No filler or redundancy.

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?

Adequate for a simple listing operation with well-documented parameters, but lacks explanation of the Athena/Glue Data Catalog relationship, pagination behavior, and return value structure. Given the tool's simplicity and 100% schema coverage, it meets minimum viability but has clear expansion opportunities.

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?

Input schema has 100% description coverage (profile, region, catalog_name, max_results all documented). The description does not add semantic meaning beyond the schema, but the baseline score of 3 applies since the schema comprehensively documents parameter purposes.

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 uses a specific verb ('List') with clear resource ('databases') and scope ('Athena data catalog'). However, it fails to distinguish from sibling tool 'aws_glue_get_databases' (which also lists databases), missing the important context that Athena queries the Glue Data Catalog and when to prefer one over the other.

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 like 'aws_glue_get_databases', or when the optional parameters (profile, region) should be specified. No mention of prerequisites like AWS credentials or IAM permissions needed.

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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