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nikhil-ganage

MCP Server Airflow Token

get_pool

Retrieve a specific Airflow connection pool by its name to manage and configure resource allocation within Apache Airflow deployments.

Instructions

Get a pool by name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pool_nameYes

Implementation Reference

  • The async handler function that implements the core logic of the 'get_pool' tool. It takes a pool_name parameter, calls the Airflow PoolApi to retrieve the pool, and returns the details as TextContent.
    async def get_pool(
        pool_name: str,
    ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        """
        Get a pool by name.
    
        Args:
            pool_name: The pool name.
    
        Returns:
            The pool details.
        """
        response = pool_api.get_pool(pool_name=pool_name)
        return [types.TextContent(type="text", text=str(response.to_dict()))]
  • The registration tuple for the 'get_pool' tool within the get_all_functions list, specifying the handler function, tool name, description, and read-only status.
    (get_pool, "get_pool", "Get a pool by name", True),
  • Helper function get_all_functions that returns the list of tool tuples for the pool API, including the 'get_pool' tool, which is used for registration.
    def get_all_functions() -> list[tuple[Callable, str, str, bool]]:
        """Return list of (function, name, description, is_read_only) tuples for registration."""
        return [
            (get_pools, "get_pools", "List pools", True),
            (get_pool, "get_pool", "Get a pool by name", True),
            (delete_pool, "delete_pool", "Delete a pool", False),
            (post_pool, "post_pool", "Create a pool", False),
            (patch_pool, "patch_pool", "Update a pool", False),
        ]
  • src/main.py:90-91 (registration)
    The registration loop in main.py that calls app.add_tool for each tool from get_pool_functions (among others), effectively registering the 'get_pool' tool.
    for func, name, description, *_ in functions:
        app.add_tool(func, name=name, description=description)
  • Mapping in APITYPE_TO_FUNCTIONS that associates APIType.POOL with get_pool_functions (aliased get_all_functions from pool.py), enabling its use in registration.
    APIType.POOL: get_pool_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 a read operation ('Get'), which implies non-destructive behavior, but doesn't disclose permissions needed, rate limits, error handling, or what data is returned. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 ('Get a pool by name') with zero wasted words, making it easy to parse. It's front-loaded with the core action, though brevity may contribute to gaps in other dimensions.

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, no output schema, and low schema coverage (0%), the description is incomplete. It doesn't explain what a 'pool' is, what data is returned, error scenarios, or how it fits with siblings like 'get_pools'. For a retrieval tool in a complex system (Airflow-like context inferred from siblings), more context is needed.

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 ('pool_name') undocumented in the schema. The description adds minimal semantics by implying the parameter is used to identify a pool by name, but doesn't explain format, constraints, or examples (e.g., case sensitivity, allowed characters). It partially compensates but not fully for the coverage gap.

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 pool by name' clearly states the verb ('Get') and resource ('pool'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_pools' (plural) or explain what a 'pool' represents in this context, leaving some ambiguity about scope.

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 like 'get_pools' (which likely lists multiple pools). The description implies retrieval by name but doesn't specify prerequisites, error conditions, or contextual triggers for usage.

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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