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nikhil-ganage

MCP Server Airflow Token

get_providers

Retrieve a list of loaded providers from Apache Airflow deployments to manage and monitor available data processing services.

Instructions

Get a list of loaded providers

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo

Implementation Reference

  • The main asynchronous handler function that implements the logic for the 'get_providers' tool. It constructs parameters from inputs, calls the external ProviderApi, and formats the response as MCP TextContent.
    async def get_providers(
        limit: Optional[int] = None,
        offset: Optional[int] = None,
    ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        """
        Get a list of providers.
    
        Args:
            limit: The numbers of items to return.
            offset: The number of items to skip before starting to collect the result set.
    
        Returns:
            A list of providers with their details.
        """
        # Build parameters dictionary
        kwargs: Dict[str, Any] = {}
        if limit is not None:
            kwargs["limit"] = limit
        if offset is not None:
            kwargs["offset"] = offset
    
        response = provider_api.get_providers(**kwargs)
        return [types.TextContent(type="text", text=str(response.to_dict()))]
  • Module-level registration function that returns the tuple defining the 'get_providers' tool for inclusion in the MCP toolset.
    def get_all_functions() -> list[tuple[Callable, str, str, bool]]:
        """Return list of (function, name, description, is_read_only) tuples for registration."""
        return [
            (get_providers, "get_providers", "Get a list of loaded providers", True),
        ]
  • src/main.py:90-92 (registration)
    The generic loop in main() that registers all collected tools (including 'get_providers' from providers) to the MCP app using app.add_tool.
    for func, name, description, *_ in functions:
        app.add_tool(func, name=name, description=description)
  • src/main.py:22-38 (registration)
    Central mapping that links APIType.PROVIDER to the provider module's get_all_functions, enabling registration of 'get_providers'.
    APITYPE_TO_FUNCTIONS = {
        APIType.CONFIG: get_config_functions,
        APIType.CONNECTION: get_connection_functions,
        APIType.DAG: get_dag_functions,
        APIType.DAGRUN: get_dagrun_functions,
        APIType.DAGSTATS: get_dagstats_functions,
        APIType.DATASET: get_dataset_functions,
        APIType.EVENTLOG: get_eventlog_functions,
        APIType.IMPORTERROR: get_importerror_functions,
        APIType.MONITORING: get_monitoring_functions,
        APIType.PLUGIN: get_plugin_functions,
        APIType.POOL: get_pool_functions,
        APIType.PROVIDER: get_provider_functions,
        APIType.TASKINSTANCE: get_taskinstance_functions,
        APIType.VARIABLE: get_variable_functions,
        APIType.XCOM: get_xcom_functions,
    }
  • src/main.py:16-16 (registration)
    Import of the provider module's get_all_functions, which includes 'get_providers', into the main registration system.
    from src.airflow.provider import get_all_functions as get_provider_functions
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'Get a list' which implies a read-only operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or what 'loaded' means (e.g., active vs. all providers). The description adds minimal context beyond the basic action.

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?

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action, though it could be slightly more specific (e.g., 'Get a paginated list of loaded data providers'). Every word earns its place, but it's borderline under-specified rather than concise.

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 no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain what 'providers' are, how they're used, or what the return format looks like. For a tool with parameters and in a context with many siblings, more detail is needed to guide 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%, so the schema provides no parameter details. The description doesn't mention parameters at all, failing to compensate for the coverage gap. With 2 parameters (limit and offset) that control pagination, the description should explain their purpose (e.g., to paginate through providers) but doesn't add any meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get a list of loaded providers' states a clear verb ('Get') and resource ('loaded providers'), but it's somewhat vague about what 'providers' are in this context (e.g., data providers, service providers) and doesn't distinguish from siblings like 'get_plugins' or 'get_connection'. It avoids tautology by not just restating the name 'get_providers'.

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. With many sibling tools like 'get_plugins' or 'get_connection', there's no indication of context, prerequisites, or exclusions. Usage is implied only by the name and description, lacking explicit instructions.

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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