MCP-Airflow-API

list_tasks

List all tasks in an Apache Airflow DAG by supplying its dag_id, enabling quick inspection of workflow components.

Instructions

[Tool Role]: Lists all tasks within the specified DAG.

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": {
      "dag_id": "<dag_id>"
    },
    "name": "list_tasks"
  }
}

Input Schema

Name	Required	Description	Default
`dag_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.0Jul 31, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description must carry the burden. It only says what the tool does, not how it behaves. It doesn't mention whether it's read-only, the return format, pagination, permissions, or any side effects. For a simple listing tool this is minimal but still lacks useful context.

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 concise sentence that adds value. It's not overly verbose, but it lacks any structure or additional sections. For such a simple tool, this is acceptable conciseness, though it could be slightly more informative.

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?

Given the existence of an output schema, return values are covered, but the description is too sparse to be complete. It doesn't clarify what 'tasks' means in this context (likely task definitions) versus task instances, and it doesn't distinguish from similar list tools. The tool has one parameter and no annotations, so the description needs to provide more context.

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 description coverage is 0%, so the description must compensate. It mentions 'specified DAG', which maps to the dag_id parameter, giving it meaning. However, it doesn't add details about the parameter's format, constraints, or possible values beyond the schema's type.

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 tool's function: 'Lists all tasks within the specified DAG.' It specifies a verb (lists) and resource (tasks in a DAG), which distinguishes it from list_dags (which lists DAGs). However, it does not explicitly differentiate from sibling tools like list_task_instances_all, which could cause confusion.

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 this tool versus alternatives. It doesn't mention conditions, exclusions, or related tools. There is no 'when to use' or 'instead use X' context.

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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