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qBittorrent MCP Server

list_search_plugins

Display all available torrent search plugins and their current status to enable efficient torrent discovery within qBittorrent.

Instructions

List all available search plugins in qBittorrent.

Returns: List of search plugins with their status

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • main.py:195-217 (handler)
    The main handler function for the 'list_search_plugins' tool. It uses the qBittorrent client to fetch available search plugins, formats them into a list of dictionaries with name, version, enabled status, URL, and supported categories, and returns the list. The @mcp.tool() decorator registers it as an MCP tool.
    @mcp.tool()
    def list_search_plugins() -> list[dict[str, Any]]:
        """
        List all available search plugins in qBittorrent.
    
        Returns:
            List of search plugins with their status
        """
        client = get_qbt_client()
    
        plugins = client.search_plugins()
    
        result = []
        for plugin in plugins:
            result.append({
                "name": plugin.name,
                "version": plugin.version,
                "enabled": plugin.enabled,
                "url": plugin.url,
                "supported_categories": plugin.supportedCategories
            })
    
        return result
  • main.py:195-195 (registration)
    Registration of the 'list_search_plugins' tool using the FastMCP @mcp.tool() decorator.
    @mcp.tool()
  • main.py:17-38 (helper)
    Helper function to get or initialize the qBittorrent client instance, used by the list_search_plugins tool.
    def get_qbt_client():
        """Get or create qBittorrent client instance."""
        global qbt_client
    
        if qbt_client is None:
            host = os.getenv("QBITTORRENT_HOST", "http://localhost:8080")
            username = os.getenv("QBITTORRENT_USERNAME", "admin")
            password = os.getenv("QBITTORRENT_PASSWORD", "adminadmin")
    
            qbt_client = qbittorrentapi.Client(
                host=host,
                username=username,
                password=password
            )
    
            try:
                qbt_client.auth_log_in()
            except qbittorrentapi.LoginFailed as e:
                raise Exception(f"Failed to login to qBittorrent: {e}")
    
        return qbt_client
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the tool lists search plugins with their status, which implies a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error conditions, or what 'status' entails. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 concise and front-loaded: the first sentence clearly states the purpose. The second sentence adds return value information, which is useful but could be integrated more smoothly. There's minimal waste, though it could be slightly more polished in structure.

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

Completeness3/5

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

Given the tool's low complexity (0 parameters) and the presence of an output schema, the description is somewhat complete. It states what the tool does and hints at the return format. However, with no annotations and behavioral gaps, it doesn't fully compensate for the lack of structured data, leaving room for improvement in transparency.

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

Parameters4/5

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

The tool has 0 parameters, with 100% schema description coverage (since there are no parameters to describe). The description doesn't need to add parameter semantics, so it meets the baseline for a parameterless tool. No additional value is required beyond stating the action.

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: 'List all available search plugins in qBittorrent.' It specifies the verb ('List') and resource ('search plugins'), and includes the scope ('all available'). However, it doesn't explicitly differentiate from sibling tools, which are mostly torrent management tools rather than search plugin tools, so the distinction is implicit rather than explicit.

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. It doesn't mention prerequisites, timing, or related tools. Given the sibling tools focus on torrent operations, this tool stands alone for search plugins, but no explicit usage context is provided.

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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