Skip to main content
Glama
Sign In
MCP-Airflow-API

MCP-Airflow-API

by fastmcp-me
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

trigger_dag

Triggers a new DAG run for a specified Airflow DAG ID, enabling immediate workflow execution and management through natural language commands.

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_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.0

TDQS

B3.1/5.0
Behavior2/5

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

Since no annotations are provided, the description bears full responsibility for disclosing side effects. It merely states the action without noting asynchronous behavior, permission requirements, failure modes, or whether the trigger is a mutation. This is insufficient for a trigger tool.

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 a single, clear sentence with no redundancy. Front-loaded with a role label, it efficiently communicates the core function.

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 lack of annotations and minimal description, the tool is underspecified. The output schema exists but the description alone does not clarify what happens after triggering (e.g., returns a run ID) or how to confirm success.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate. It only relates dag_id to 'specified Airflow DAG' but doesn't explain format, valid values, or behavior if the DAG doesn't exist. Minimal added meaning.

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 tool's function with a specific verb ('Triggers') and resource ('a new DAG run') for a specified Airflow DAG. It unambiguously distinguishes this from sibling tools like get_dag or pause_dag, which don't trigger runs.

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, when not to, or how it compares to alternatives. It only states the tool role without context, prerequisites, or references to other tools.

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

Deploy Server

Other Tools