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nikhil-ganage

MCP Server Airflow Token

list_connections

Retrieve and display all configured connections from Apache Airflow deployments, enabling management of data pipeline integrations.

Instructions

List all connections

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
order_byNo

Implementation Reference

  • The main handler function for the 'list_connections' tool. It accepts optional parameters limit, offset, and order_by, constructs kwargs, calls connection_api.get_connections, and returns the response as TextContent.
    async def list_connections(
        limit: Optional[int] = None,
        offset: Optional[int] = None,
        order_by: Optional[str] = None,
    ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        # Build parameters dictionary
        kwargs: Dict[str, Any] = {}
        if limit is not None:
            kwargs["limit"] = limit
        if offset is not None:
            kwargs["offset"] = offset
        if order_by is not None:
            kwargs["order_by"] = order_by
    
        response = connection_api.get_connections(**kwargs)
        return [types.TextContent(type="text", text=str(response.to_dict()))]
  • Registers the list_connections tool (along with related connection tools) by returning a tuple of (function, name, description, read_only=True) which is later used in main.py to add_tool to the MCP app.
    def get_all_functions() -> list[tuple[Callable, str, str, bool]]:
        """Return list of (function, name, description, is_read_only) tuples for registration."""
        return [
            (list_connections, "list_connections", "List all connections", True),
            (create_connection, "create_connection", "Create a connection", False),
            (get_connection, "get_connection", "Get a connection by ID", True),
            (update_connection, "update_connection", "Update a connection by ID", False),
            (delete_connection, "delete_connection", "Delete a connection by ID", False),
            (test_connection, "test_connection", "Test a connection", True),
        ]
  • src/main.py:90-92 (registration)
    The generic registration loop in main.py that calls app.add_tool for each tool from the modules' get_all_functions, including list_connections.
    for func, name, description, *_ in functions:
        app.add_tool(func, name=name, description=description)
  • Initializes the connection_api instance used by the list_connections handler, imported from airflow_client.
    connection_api = ConnectionApi(api_client)
Behavior1/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. 'List all connections' reveals nothing about permissions needed, rate limits, pagination behavior (despite limit/offset parameters), response format, or whether this is a read-only operation. For a tool with 3 parameters and no annotation coverage, this is a significant gap in behavioral transparency.

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 maximally concise at three words, with no wasted language. It's front-loaded with the core action and resource. While under-specified, it achieves perfect efficiency within its limited scope.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 3 parameters with 0% schema coverage, no annotations, no output schema, and multiple sibling tools in a complex server environment, the description is completely inadequate. It doesn't explain what 'connections' are, how results are returned, parameter usage, or behavioral characteristics. For a list operation in what appears to be an Airflow/ETL context, this leaves critical gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (parameters have only titles, no descriptions), and the description provides zero information about the three parameters (limit, offset, order_by). The description doesn't mention pagination, sorting, or any parameter usage at all. With 3 undocumented parameters and no compensation in the description, this fails to add value beyond the bare 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 'List all connections' clearly states the verb ('List') and resource ('connections'), making the basic purpose understandable. However, it lacks specificity about what 'connections' are in this context and doesn't differentiate from sibling tools like 'get_connection' (which retrieves a single connection). The description is functional but vague 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?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_connection' (for single connection retrieval) and 'test_connection' (for validation), the agent receives no explicit or implied direction about when this list operation is appropriate versus those alternatives. No prerequisites, exclusions, or comparative context is mentioned.

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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