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MCP-Airflow-API

MCP-Airflow-API

by call518
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

trigger_dag

Starts a new run for an Airflow DAG using its exact DAG identifier, enabling on-demand pipeline execution through MCP.

Instructions

[Tool Role]: Triggers a new DAG run for a specified Airflow 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": "trigger_dag"
  }
}

Input Schema

NameRequiredDescriptionDefault
dag_idYesExact DAG identifier, as returned by list_dags; not its display name.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.7.4
    • addedInput schema / properties / dag_id / description
      Added value: +"Exact DAG identifier, as returned by list_dags; not its\ndisplay name."
  2. Addedv3.7.2
  3. Removedv3.6.5
  4. Changed2 schema fields changedv3.6.6
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / dag_id / title
      Removed value: -"Dag Id"
  5. First observed

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 carries the full burden for a mutation tool. It states that a new run is triggered, but does not disclose permission requirements, whether the trigger is synchronous or asynchronous, idempotency behavior, or what happens if the DAG is paused.

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, front-loaded sentence with no filler or repetition. It is concise and easy to scan, though the bracketed tool-role label adds little informational value.

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?

The tool has low parameter complexity, complete schema coverage, and an output schema, so the description need not explain return values. However, for a mutation tool with no annotations, it is still thinner than ideal because it omits basic behavioral context about triggering a DAG run.

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 100%, and dag_id already documents that it must be the exact identifier returned by list_dags rather than a display name. The description adds no parameter semantics beyond "specified Airflow DAG," so baseline 3 is appropriate.

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 and resource: "Triggers a new DAG run" for a specified Airflow DAG. It is clear what the tool does, though it does not explicitly differentiate itself from nearby tools such as pause_dag, unpause_dag, or list_dags.

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 gives no guidance on when to use this tool versus alternatives, prerequisites for triggering a DAG, or whether the caller should confirm the DAG state first. The only usage hint is that the DAG must be specified.

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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