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airflow-mcp-server

airflow-mcp-server

by us-all
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

airflow-get-task-logs

Fetch the tail of an Airflow task instance log to quickly review the most recent output or errors for a specific try number.

Instructions

Fetch the tail (last N kB) of an Airflow task instance log for a specific try_number

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": {
      "dagId": "<dagId>",
      "dagRunId": "<dagRunId>",
      "taskId": "<taskId>"
    },
    "name": "airflow-get-task-logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
dagIdYes
dagRunIdYes
taskIdYes
tryNumberNo
tailKbNoReturn only the last N kilobytes of log
extractFieldsNoComma-separated dotted paths to project from response (e.g. 'id,name,owner.name,columns.*.name'). Use `*` as wildcard for arrays/objects. Wrap field names with dots in backticks. Reduces response tokens dramatically on large entities.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.4
  2. Removedv1.0.2
  3. Changed1 schema field changedv1.0.0
    • addedInput schema / properties / extractFields
      Added value: +{
+  "description": "Comma-separated dotted paths to project from response (e.g. 'id,name,owner.name,columns.*.name'). Use `*` as wildcard for arrays/objects. Wrap field names with dots in backticks. Reduces response tokens dramatically on large entities.",
+  "type": "string"
+}
  4. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It mentions 'tail (last N kB)' implying it returns a truncated portion of the log, but it does not describe permissions, rate limits, response format, or what happens if the log is smaller than tailKb. This is insufficient for safe invocation.

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, well-structured sentence that front-loads the action and resource. It contains no extraneous information and is easily parseable by an AI agent.

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 tool has 6 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain return values (e.g., log content format), error conditions, or behavior when parameters are missing or invalid. The agent would need additional context to use the tool effectively.

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 low (33%, only tailKb and extractFields are described). The description adds value by explaining 'tail' and mentioning 'try_number', which relates to the tryNumber parameter. However, it does not elaborate on dagId, dagRunId, or taskId beyond their names, leaving the agent to infer their purposes from context.

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 action ('Fetch'), the resource ('tail of Airflow task instance log'), and the specific context ('for a specific try_number'). It effectively distinguishes itself from sibling tools like airflow-clear-task or airflow-list-dags, which handle different aspects of Airflow.

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 is provided on when to use this tool versus alternatives. There is no mention of prerequisites, such as needing a successful task run or that logs are only available after execution. The description lacks context for appropriate 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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