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GodisinHisHeaven

USCardForum MCP Server

get_categories

Retrieve a complete mapping of forum categories to organize topics by subject area, enabling users to filter search results and navigate specific sections like credit card applications, bank bonuses, and travel discussions.

Instructions

Get a mapping of all forum categories.

Returns a CategoryMap object with category_id to category name mapping.
Categories organize topics by subject area.

Common USCardForum categories include sections for:
- Credit card applications and approvals
- Bank account bonuses
- Travel and redemptions
- Data points and experiences

Use category IDs to:
- Filter search results by category
- Understand which section a topic belongs to
- Navigate to specific areas of interest

The mapping includes both main categories and subcategories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoriesNoID to name mapping

Implementation Reference

  • MCP tool handler for get_categories: decorated function that fetches and returns CategoryMap using get_client().
    @mcp.tool()
    def get_categories() -> CategoryMap:
        """
        Get a mapping of all forum categories.
    
        Returns a CategoryMap object with category_id to category name mapping.
        Categories organize topics by subject area.
    
        Common USCardForum categories include sections for:
        - Credit card applications and approvals
        - Bank account bonuses
        - Travel and redemptions
        - Data points and experiences
    
        Use category IDs to:
        - Filter search results by category
        - Understand which section a topic belongs to
        - Navigate to specific areas of interest
    
        The mapping includes both main categories and subcategories.
        """
        return get_client().get_category_map()
    
    
    __all__ = ["get_categories"]
  • Import of get_categories (line 21) in server.py registers the tool for the MCP server.
    from uscardforum.server_tools import (
        analyze_user,
        bookmark_post,
        compare_cards,
        find_data_points,
        get_all_topic_posts,
        get_categories,
        get_current_session,
        get_hot_topics,
        get_new_topics,
        get_notifications,
        get_top_topics,
        get_topic_info,
        get_topic_posts,
        get_user_actions,
        get_user_badges,
        get_user_followers,
        get_user_following,
        get_user_reactions,
        get_user_replies,
        get_user_summary,
        get_user_topics,
        list_users_with_badge,
        login,
        research_topic,
        resource_categories,
        resource_hot_topics,
        resource_new_topics,
        search_forum,
        subscribe_topic,
    )
  • Pydantic BaseModel CategoryMap defines the output schema for the tool: dict[int, str] of category_id to name.
    class CategoryMap(BaseModel):
        """Mapping of category IDs to names."""
    
        categories: dict[int, str] = Field(
            default_factory=dict, description="ID to name mapping"
        )
    
        def get_name(self, category_id: int) -> str | None:
            """Get category name by ID."""
            return self.categories.get(category_id)
    
        def __getitem__(self, category_id: int) -> str:
            """Get category name by ID."""
            return self.categories[category_id]
    
        def __contains__(self, category_id: int) -> bool:
            """Check if category ID exists."""
            return category_id in self.categories
    
        def items(self):
            """Iterate over category mappings."""
            return self.categories.items()
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by specifying the return type ('CategoryMap object'), scope ('all forum categories'), and structure ('includes both main categories and subcategories'). It doesn't mention rate limits, authentication needs, or potential errors, but provides solid operational context.

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 efficiently structured with clear sections: purpose statement, return specification, context examples, and usage scenarios. Every sentence adds value without redundancy, and it's appropriately sized for the tool's complexity.

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

Completeness5/5

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

Given the tool has no parameters, an output schema exists, and the description thoroughly explains what the tool does, its return format, real-world examples, and use cases, this provides complete contextual understanding for an AI agent to correctly invoke this tool.

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?

With 0 parameters and 100% schema coverage, the baseline would be 4. The description appropriately doesn't discuss parameters since none exist, instead focusing on the tool's purpose and output.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Get a mapping'), resource ('all forum categories'), and output format ('CategoryMap object with category_id to category name mapping'). It distinguishes this tool from siblings like get_hot_topics or get_new_topics by focusing on category metadata rather than topic content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool by listing specific use cases: filtering search results, understanding topic sections, and navigation. However, it doesn't explicitly state when NOT to use it or name alternative tools for related functions.

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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