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yangkyeongmo

MCP Server for Apache Airflow

by yangkyeongmo

get_plugins

Retrieve a list of loaded plugins from Apache Airflow to manage and monitor plugin configurations within your workflow system.

Instructions

Get a list of loaded plugins

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo

Implementation Reference

  • The main handler function for the 'get_plugins' MCP tool. It accepts optional limit and offset parameters, calls the Airflow PluginApi.get_plugins, and returns the response as a TextContent list.
    async def get_plugins(
        limit: Optional[int] = None,
        offset: Optional[int] = None,
    ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        """
        Get a list of loaded plugins.
    
        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 loaded plugins.
        """
        # Build parameters dictionary
        kwargs: Dict[str, Any] = {}
        if limit is not None:
            kwargs["limit"] = limit
        if offset is not None:
            kwargs["offset"] = offset
    
        response = plugin_api.get_plugins(**kwargs)
        return [types.TextContent(type="text", text=str(response.to_dict()))]
  • The get_all_functions helper that provides the registration tuple (function, name, description, read_only) for the 'get_plugins' tool, imported and used in main.py to register the tool with the MCP server.
    def get_all_functions() -> list[tuple[Callable, str, str, bool]]:
        """Return list of (function, name, description, is_read_only) tuples for registration."""
        return [
            (get_plugins, "get_plugins", "Get a list of loaded plugins", True),
        ]
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 for behavioral disclosure. 'Get a list' implies a read-only operation, but it doesn't specify whether this requires authentication, what format the list returns (names, metadata, status), whether it's paginated, or if there are rate limits. 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 a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a simple list operation. Every word earns its place, making it easy to parse quickly.

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 simplicity (2 optional parameters, no output schema, no annotations), the description is incomplete. It doesn't explain what 'loaded plugins' means in this context, what information is returned, or how the parameters affect the result. For even a basic list tool, more context about the return format and parameter usage would be helpful.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. However, the description mentions nothing about the 'limit' and 'offset' parameters shown in the schema. While 'Get a list' implies potential pagination, it doesn't explicitly connect to these parameters or explain their purpose. The description adds no value beyond what's inferred from the schema structure.

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 verb ('Get') and resource ('list of loaded plugins'), making the purpose immediately understandable. It distinguishes itself from sibling tools that mostly deal with DAGs, connections, datasets, and variables rather than plugins. However, it doesn't specify what information about plugins is returned or the scope of 'loaded' (e.g., active vs. all available).

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 available (like get_providers, get_config, get_version), there's no indication of when plugins specifically should be queried versus other system components. No prerequisites, exclusions, or comparison to similar tools are 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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