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rhettlong

USCardForum MCP Server

by rhettlong

search_forum

Search USCardForum for credit card discussions using queries with operators like in:title, @username, category:name, and sort by relevance, latest, views, or activity.

Instructions

Search USCardForum for topics and posts matching a query.

Args:
    query: Search query string. Supports Discourse operators:
        - Basic: "chase sapphire bonus"
        - In title only: "chase sapphire in:title"
        - By author: "@username chase"
        - In category: "category:credit-cards chase"
        - With tag: "#amex bonus"
        - Exact phrase: '"sign up bonus"'
        - Exclude: "chase -sapphire"
        - Time: "after:2024-01-01" or "before:2024-06-01"

    page: Page number for pagination (starts at 1)

    order: Sort order for results. Options:
        - "relevance": Best match (default)
        - "latest": Most recent first
        - "views": Most viewed
        - "likes": Most liked
        - "activity": Recent activity
        - "posts": Most replies

Returns a SearchResult object with:
- posts: List of matching SearchPost objects with excerpts
- topics: List of matching SearchTopic objects
- users: List of matching SearchUser objects
- grouped_search_result: Metadata about result counts

Example queries:
- "Chase Sapphire Reserve order:latest" - Recent CSR discussions
- "AMEX popup in:title" - Topics about AMEX popup in title
- "data point category:credit-cards" - Data points in CC category
- "@expert_user order:likes" - Most liked posts by a user

Pagination: If more results exist, increment page parameter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query string. Supports operators: 'in:title', '@username', 'category:name', '#tag', 'after:date', 'before:date'
pageNoPage number for pagination (starts at 1)
orderNoSort order: 'relevance' (default), 'latest', 'views', 'likes', 'activity', or 'posts'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
postsNoMatching posts
usersNoMatching users
topicsNoMatching topics
grouped_search_resultNoResult metadata

Implementation Reference

  • The core handler function for the 'search_forum' tool, decorated with @mcp.tool(). It defines input parameters with descriptions (schema) and implements the logic by calling the client's search method.
    @mcp.tool()
    def search_forum(
        query: Annotated[
            str,
            Field(
                description="Search query string. Supports operators: 'in:title', '@username', 'category:name', '#tag', 'after:date', 'before:date'"
            ),
        ],
        page: Annotated[
            int | None,
            Field(default=None, description="Page number for pagination (starts at 1)"),
        ] = None,
        order: Annotated[
            str | None,
            Field(
                default=None,
                description="Sort order: 'relevance' (default), 'latest', 'views', 'likes', 'activity', or 'posts'",
            ),
        ] = None,
    ) -> SearchResult:
        """
        Search USCardForum for topics and posts matching a query.
    
        Args:
            query: Search query string. Supports Discourse operators:
                - Basic: "chase sapphire bonus"
                - In title only: "chase sapphire in:title"
                - By author: "@username chase"
                - In category: "category:credit-cards chase"
                - With tag: "#amex bonus"
                - Exact phrase: '"sign up bonus"'
                - Exclude: "chase -sapphire"
                - Time: "after:2024-01-01" or "before:2024-06-01"
    
            page: Page number for pagination (starts at 1)
    
            order: Sort order for results. Options:
                - "relevance": Best match (default)
                - "latest": Most recent first
                - "views": Most viewed
                - "likes": Most liked
                - "activity": Recent activity
                - "posts": Most replies
    
        Returns a SearchResult object with:
        - posts: List of matching SearchPost objects with excerpts
        - topics: List of matching SearchTopic objects
        - users: List of matching SearchUser objects
        - grouped_search_result: Metadata about result counts
    
        Example queries:
        - "Chase Sapphire Reserve order:latest" - Recent CSR discussions
        - "AMEX popup in:title" - Topics about AMEX popup in title
        - "data point category:credit-cards" - Data points in CC category
        - "@expert_user order:likes" - Most liked posts by a user
    
        Pagination: If more results exist, increment page parameter.
        """
        return get_client().search(query, page=page, order=order)
  • Pydantic BaseModel for SearchResult, defining the output schema of the tool, along with component models (SearchPost, SearchTopic, etc.) defined earlier in the file.
    class SearchResult(BaseModel):
        """Complete search results."""
    
        posts: list[SearchPost] = Field(default_factory=list, description="Matching posts")
        topics: list[SearchTopic] = Field(
            default_factory=list, description="Matching topics"
        )
        users: list[SearchUser] = Field(default_factory=list, description="Matching users")
        grouped_search_result: GroupedSearchResult | None = Field(
            None, description="Result metadata"
        )
    
        class Config:
            extra = "ignore"
    
        @classmethod
        def from_api_response(cls, data: dict[str, Any]) -> "SearchResult":
            """Parse from raw API response."""
            posts = [SearchPost(**p) for p in data.get("posts", [])]
            topics = [SearchTopic(**t) for t in data.get("topics", [])]
            users = [SearchUser(**u) for u in data.get("users", [])]
    
            grouped = None
            if "grouped_search_result" in data:
                grouped = GroupedSearchResult(**data["grouped_search_result"])
    
            return cls(
                posts=posts,
                topics=topics,
                users=users,
                grouped_search_result=grouped,
            )
  • Imports the search_forum function into the server_tools package __init__.py for exposure and registration in the MCP server.
    from .topics import get_hot_topics, get_new_topics, get_top_topics
    from .search import search_forum
    from .categories import get_categories
  • Lists 'search_forum' in the __all__ export of the main server module, ensuring it's registered as an available MCP tool.
    "search_forum",
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly describes the tool's behavior: it explains the return format (SearchResult object with posts, topics, users, and metadata), pagination handling ('If more results exist, increment page parameter'), and search capabilities (including operators and sorting options), covering aspects like output structure and operational constraints.

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 well-structured with clear sections (Args, Returns, Example queries, Pagination) and is appropriately sized for a search tool with multiple parameters and complex functionality. However, it could be slightly more concise by integrating some details (e.g., merging operator examples into the query description) without losing clarity.

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's complexity (3 parameters, no annotations, but with an output schema), the description is complete. It covers purpose, usage, parameters with examples, return values (leveraging the output schema for structure), and behavioral aspects like pagination, ensuring the agent has all necessary information to use the tool effectively.

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

Parameters5/5

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

The description adds significant value beyond the input schema, which has 100% coverage but minimal detail. It elaborates on the query parameter with specific operator examples and syntax, details the order parameter with all sort options and their meanings, and clarifies pagination usage for the page parameter, providing practical guidance not present in the schema descriptions.

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 tool's purpose: 'Search USCardForum for topics and posts matching a query.' It specifies the verb ('search'), resource ('USCardForum'), and scope ('topics and posts'), distinguishing it from sibling tools like get_hot_topics or get_new_topics that retrieve predefined lists rather than performing custom searches.

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 (searching with queries and operators) and includes example queries. However, it does not explicitly state when not to use it or name specific alternatives among the sibling tools, such as get_topic_info for detailed topic information instead of search results.

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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