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list_variables

Retrieve all variables stored in Apache Airflow for configuration management and workflow parameter access.

Instructions

[Tool Role]: Lists all variables in Airflow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The primary handler function for the 'list_variables' MCP tool. Decorated with @mcp.tool() for automatic registration. Fetches Airflow variables via the REST API with optional pagination parameters (limit and offset).
    @mcp.tool()
    async def list_variables(limit: int = 20, offset: int = 0) -> Dict[str, Any]:
        """[Tool Role]: Lists all variables in Airflow."""
        params = {'limit': limit, 'offset': offset}
        query_string = "&".join([f"{k}={v}" for k, v in params.items()])
        resp = await airflow_request("GET", f"/variables?{query_string}")
        resp.raise_for_status()
        return resp.json()
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but doesn't describe the return format, pagination behavior, permissions required, or any side effects. This is inadequate for a tool with parameters and an output schema.

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 extremely concise with a single sentence that directly states the tool's role. It's front-loaded and wastes no words, making it efficient for quick understanding.

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 parameters and an output schema, the description is incomplete. It doesn't address parameter usage, return values, or behavioral context, relying too heavily on the structured data without compensating in the description.

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?

The input schema has 0% description coverage, and the tool description doesn't mention the parameters at all. It fails to explain what 'limit' and 'offset' do or how they affect the listing, leaving them undocumented despite their presence.

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 clearly states the tool's purpose with a specific verb ('Lists') and resource ('all variables in Airflow'), making it immediately understandable. However, it doesn't differentiate from its sibling 'get_variable', which retrieves a single variable, so it misses full sibling distinction.

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 versus alternatives like 'get_variable' or other list tools. It lacks context about use cases, prerequisites, or exclusions, leaving the agent with no usage direction.

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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