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Airflow MCP

Airflow MCP

by zamax14
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_task_logs

Retrieve logs for any Airflow task instance by specifying DAG ID, run ID, and task ID. Output is truncated to the system's maximum log line setting.

Instructions

Get logs for a task instance, truncated to AIRFLOW_LOG_MAX_LINES.

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>",
      "dag_run_id": "<dag_run_id>",
      "task_id": "<task_id>"
    },
    "name": "get_task_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
dag_idYes
task_idYes
dag_run_idYes
try_numberNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

Discloses truncation to AIRFLOW_LOG_MAX_LINES, a key behavioral detail. However, no information about permissions, side effects, or error conditions.

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?

Single sentence is efficient, but could include structured details. No fluff, but under-specification for a tool with 4 parameters.

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?

Despite having an output schema, the description is too minimal. It omits parameter explanations and usage context, leaving gaps for the agent.

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

Parameters1/5

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

Schema coverage is 0%, and the description does not explain any parameter. Parameter names are non-obvious (e.g., dag_run_id), requiring the agent to infer 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 it retrieves logs for a task instance and mentions truncation. It is specific and distinguishes from sibling tools which handle DAGs and 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?

No guidance on when to use this tool versus alternatives or when not to use it. No context about prerequisites or typical use cases.

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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