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yangkyeongmo

MCP Server for Apache Airflow

by yangkyeongmo

delete_variable

Remove variables from Apache Airflow by specifying their key. This tool helps manage Airflow configurations by deleting stored variables through the MCP server interface.

Instructions

Delete a variable by key

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes

Implementation Reference

  • The main handler function for the 'delete_variable' tool. It takes a key parameter, calls the Airflow VariableApi to delete the variable, and returns a text content response with the result.
    async def delete_variable(key: str) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        response = variable_api.delete_variable(variable_key=key)
        return [types.TextContent(type="text", text=str(response.to_dict()))]
  • Registers the 'delete_variable' tool (line 18) as part of the list of variable-related tools returned by get_all_functions for MCP tool registration.
    def get_all_functions() -> list[tuple[Callable, str, str, bool]]:
        """Return list of (function, name, description, is_read_only) tuples for registration."""
        return [
            (list_variables, "list_variables", "List all variables", True),
            (create_variable, "create_variable", "Create a variable", False),
            (get_variable, "get_variable", "Get a variable by key", True),
            (update_variable, "update_variable", "Update a variable by key", False),
            (delete_variable, "delete_variable", "Delete a variable by key", False),
        ]
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. It states 'Delete' implying a destructive mutation, but does not disclose behavioral traits such as permissions required, whether deletion is permanent or reversible, error handling (e.g., if key doesn't exist), or side effects. This is a significant gap for a mutation tool with zero annotation coverage.

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, efficient sentence with zero waste—'Delete a variable by key' is front-loaded and directly conveys the core action. Every word earns its place, making it highly concise and well-structured.

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's complexity (destructive mutation), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It fails to address key aspects like behavioral transparency, parameter details, or expected outcomes, making it inadequate for safe and effective use by an AI agent.

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?

Schema description coverage is 0%, with one parameter 'key' undocumented in the schema. The description adds minimal semantics by specifying 'by key', implying the parameter identifies the variable to delete, but does not explain what 'key' represents (e.g., variable name, identifier format) or constraints. It partially compensates but leaves the parameter meaning vague.

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 'Delete a variable by key' clearly states the action (delete) and resource (variable), with the method specified (by key). It distinguishes from siblings like 'get_variable' (read) and 'update_variable' (modify), but does not explicitly differentiate from 'clear_dag_run' or other deletion tools, keeping it at 4 rather than 5.

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. It does not mention prerequisites (e.g., variable must exist), exclusions, or related tools like 'create_variable' or 'update_variable' for context. The description is purely functional without usage 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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