Skip to main content
Glama

list_dags

Retrieve and display DAGs from MWAA Airflow environments to monitor workflow status and schedules. Specify environment, limit results, or filter to active DAGs only.

Instructions

List all DAGs in the MWAA environment.

Args: env: Target environment — 'dev', 'uat', 'test', or 'prod'. IMPORTANT: Do NOT guess or default. Ask the user which environment if not specified. limit: Maximum number of DAGs to return (default 100). only_active: If True, show only unpaused DAGs.

Returns a formatted table of DAGs with schedule interval and pause status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envNo
limitNo
only_activeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it specifies the return format ('formatted table'), mentions default values for parameters, and includes an important instruction about not guessing the environment. However, it doesn't cover aspects like rate limits or error handling.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a structured breakdown of args and returns. Every sentence adds value without redundancy, making it efficient and easy to parse.

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

Completeness4/5

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

For a tool with 3 parameters, no annotations, but an output schema, the description is quite complete: it covers purpose, parameters, and return format. The output schema likely handles return values, so the description doesn't need to detail them further. Minor gaps include lack of error or edge-case handling.

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?

Given 0% schema description coverage, the description fully compensates by explaining all three parameters: 'env' with allowed values and a critical usage note, 'limit' with its default, and 'only_active' with its filtering logic. It adds substantial meaning beyond the bare 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 specific action ('List all DAGs') and resource ('in the MWAA environment'), distinguishing it from siblings like list_dag_runs, list_emr_applications, or list_job_runs. It precisely identifies what the tool does without ambiguity.

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

Usage Guidelines4/5

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

The description provides clear context for usage by specifying the target environment and filtering options, but it does not explicitly state when to use this tool versus alternatives like get_dags_status_dashboard or list_dag_runs. It offers guidance on parameter usage but lacks sibling differentiation.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SrujanReddyKallu2024/MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server