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GodisinHisHeaven

USCardForum MCP Server

get_user_following

Fetch users followed by a specific member to discover community influencers, find related experts, and map social connections on the USCardForum platform.

Instructions

Fetch the list of users that a user follows.

Args:
    username: The user's handle
    page: Page number for pagination (optional)

Returns a FollowList object with:
- users: List of FollowUser objects
- total_count: Total users being followed

Use to:
- Discover influential users in the community
- Find related experts
- Map social connections

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesThe user's handle
pageNoPage number for pagination

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
usersNoUser list
total_countNoTotal users

Implementation Reference

  • MCP tool handler for 'get_user_following'. Decorated with @mcp.tool(), defines input schema using Pydantic Annotated and Field, returns FollowList from client.
    @mcp.tool()
    def get_user_following(
        username: Annotated[
            str,
            Field(description="The user's handle"),
        ],
        page: Annotated[
            int | None,
            Field(default=None, description="Page number for pagination"),
        ] = None,
    ) -> FollowList:
        """
        Fetch the list of users that a user follows.
    
        Args:
            username: The user's handle
            page: Page number for pagination (optional)
    
        Returns a FollowList object with:
        - users: List of FollowUser objects
        - total_count: Total users being followed
    
        Use to:
        - Discover influential users in the community
        - Find related experts
        - Map social connections
        """
        return get_client().get_user_following(username, page=page)
  • Pydantic BaseModel defining the output schema FollowList, used by the tool.
    class FollowList(BaseModel):
        """List of followed/following users."""
    
        users: list[FollowUser] = Field(default_factory=list, description="User list")
        total_count: int = Field(0, description="Total users")
    
        class Config:
            extra = "ignore"
  • Re-export of get_user_following from users.py module into server_tools namespace.
    from .users import (
        get_user_summary,
        get_user_topics,
        get_user_replies,
        get_user_actions,
        get_user_badges,
        get_user_following,
        get_user_followers,
        get_user_reactions,
        list_users_with_badge,
    )
  • Import of get_user_following into main server module.
        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,
    )
    
    __all__ = [
        "MCP_HOST",
        "MCP_PORT",
        "MCP_TRANSPORT",
        "NITAN_TOKEN",
        "SERVER_INSTRUCTIONS",
        "get_client",
        "main",
        "mcp",
        "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",
  • Client method delegating to UsersAPI.get_user_following.
    def get_user_following(
        self,
        username: str,
        page: int | None = None,
    ) -> FollowList:
        """Fetch users that a user follows.
    
        Args:
            username: User handle
            page: Optional page number
    
        Returns:
            List of followed users
        """
        return self._users.get_user_following(username, page=page)
Behavior3/5

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 discloses that the tool returns a FollowList object with users and total_count, and mentions pagination via the 'page' parameter. However, it doesn't cover important behavioral aspects like rate limits, authentication requirements, error conditions, or whether it's a read-only operation (though 'fetch' implies reading).

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 well-structured with clear sections (purpose, args, returns, use cases), front-loaded with the core purpose. Every sentence earns its place—no wasted words. It's appropriately sized for a tool with two parameters and clear functionality.

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

Completeness4/5

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

Given that an output schema exists (implied by 'Returns a FollowList object'), the description doesn't need to explain return values in detail. It covers the purpose, parameters, and usage context adequately. However, as a read operation with no annotations, it could benefit from more behavioral transparency (e.g., auth needs, rate limits) to be fully complete.

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 100%, so the schema already documents both parameters fully. The description repeats the parameter info in the 'Args:' section but adds no additional meaning beyond what's in the schema (e.g., no examples, format details, or constraints). Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Fetch the list of users') and resource ('that a user follows'), distinguishing it from sibling tools like get_user_followers (which fetches followers rather than following). The verb 'fetch' is precise and the scope is well-defined.

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 'Use to:' section provides clear context for when to use this tool (e.g., 'Discover influential users', 'Find related experts'), but it doesn't explicitly state when not to use it or name alternatives (like get_user_followers for the reverse relationship). The guidance is helpful but lacks explicit exclusions.

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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