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hmumixaM

USCardForum MCP Server

by hmumixaM

get_top_topics

Retrieve top-performing forum discussions for specified time periods to identify trending or historically valuable content.

Instructions

Fetch top-performing topics for a specific time period.

Args:
    period: Time window for ranking. Must be one of:
        - "daily": Top topics from today
        - "weekly": Top topics this week
        - "monthly": Top topics this month (default)
        - "quarterly": Top topics this quarter
        - "yearly": Top topics this year
    page: Page number for pagination (0-indexed). Use page=1 to get more topics.

Use this to:
- Find the most valuable discussions in a time range
- Research historically important threads
- Identify evergreen popular content

Returns TopicSummary objects sorted by engagement score.

Example: Use "yearly" to find the most impactful discussions,
or "daily" to see what's trending today.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoTime window for ranking: 'daily', 'weekly', 'monthly' (default), 'quarterly', or 'yearly'monthly
pageNoPage number for pagination (0-indexed, default: 0)

Implementation Reference

  • MCP tool handler for 'get_top_topics'. Defines input schema with Pydantic Annotated Fields and comprehensive docstring. Executes core logic by delegating to the DiscourseClient implementation.
    @mcp.tool()
    def get_top_topics(
        period: Annotated[
            str,
            Field(
                default="monthly",
                description="Time window for ranking: 'daily', 'weekly', 'monthly' (default), 'quarterly', or 'yearly'",
            ),
        ] = "monthly",
        page: Annotated[
            int | None,
            Field(default=None, description="Page number for pagination (0-indexed, default: 0)"),
        ] = None,
    ) -> list[TopicSummary]:
        """
        Fetch top-performing topics for a specific time period.
    
        Args:
            period: Time window for ranking. Must be one of:
                - "daily": Top topics from today
                - "weekly": Top topics this week
                - "monthly": Top topics this month (default)
                - "quarterly": Top topics this quarter
                - "yearly": Top topics this year
            page: Page number for pagination (0-indexed). Use page=1 to get more topics.
    
        Use this to:
        - Find the most valuable discussions in a time range
        - Research historically important threads
        - Identify evergreen popular content
    
        Returns TopicSummary objects sorted by engagement score.
    
        Example: Use "yearly" to find the most impactful discussions,
        or "daily" to see what's trending today.
        """
        return get_client().get_top_topics(period=period, page=page)
  • Pydantic model defining the output structure for each topic in the list returned by get_top_topics.
    class TopicSummary(BaseModel):
        """Summary of a topic for list views (hot, new, top topics)."""
    
        id: int = Field(..., description="Unique topic identifier")
        title: str = Field(..., description="Topic title")
        posts_count: int = Field(0, description="Total number of posts")
        views: int = Field(0, description="Total view count")
        like_count: int = Field(0, description="Total likes on the topic")
        category_id: int | None = Field(None, description="Category identifier")
        category_name: str | None = Field(None, description="Category name")
        created_at: datetime | None = Field(None, description="When topic was created")
        last_posted_at: datetime | None = Field(None, description="Last activity time")
    
        class Config:
            extra = "ignore"
  • Explicit import of the get_top_topics tool from topics.py into the server_tools __init__, making it available for re-export and MCP server registration.
    from .topics import get_hot_topics, get_new_topics, get_top_topics
    from .search import search_forum
  • Low-level API implementation in TopicsAPI that makes HTTP request to /top.json and parses JSON response into TopicSummary objects.
    def get_top_topics(
        self, period: str = "monthly", *, page: int | None = None
    ) -> list[TopicSummary]:
        """Fetch top topics for a time period.
    
        Args:
            period: One of 'daily', 'weekly', 'monthly', 'quarterly', 'yearly'
            page: Page number for pagination (0-indexed, default: 0)
    
        Returns:
            List of top topic summaries
        """
        allowed = {"daily", "weekly", "monthly", "quarterly", "yearly"}
        if period not in allowed:
            raise ValueError(f"period must be one of {sorted(list(allowed))}")
    
        params: dict[str, Any] = {"period": period}
        if page is not None:
            params["page"] = int(page)
    
        payload = self._get(
            "/top.json",
            params=params,
            headers={"Accept": "application/json, text/plain, */*"},
        )
        topics = payload.get("topic_list", {}).get("topics", [])
        return [TopicSummary(**t) for t in topics]
  • Client wrapper that calls the API layer and enriches results with category names.
    def get_top_topics(
        self, period: str = "monthly", *, page: int | None = None
    ) -> list[TopicSummary]:
        """Fetch top topics for a time period.
    
        Args:
            period: One of 'daily', 'weekly', 'monthly', 'quarterly', 'yearly'
            page: Page number for pagination (0-indexed, default: 0)
    
        Returns:
            List of top topic summaries
        """
        topics = self._topics.get_top_topics(period=period, page=page)
        return self._enrich_with_categories(topics)

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