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GodisinHisHeaven

USCardForum MCP Server

get_user_summary

Fetch a user's profile summary to evaluate credibility, find valuable contributions, and understand participation level on USCardForum.

Instructions

Fetch a comprehensive summary of a user's profile.

Args:
    username: The user's handle (case-insensitive)

Returns a UserSummary object with:
- user_id: User ID
- username: Username
- stats: UserStats with posts, topics, likes given/received, etc.
- badges: List of recent Badge objects
- top_topics: Most successful topics
- top_replies: Most successful replies

Use this to:
- Evaluate a user's credibility and experience
- Find their most valuable contributions
- Understand their participation level

The summary provides a quick overview without fetching
individual post histories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYesThe user's handle (case-insensitive)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoDisplay name
statsNoUser statistics
badgesNoRecent badges
user_idNoUser ID
usernameNoUsername
created_atNoAccount creation date
top_topicsNoTop topics
top_repliesNoTop replies
last_seen_atNoLast seen online

Implementation Reference

  • The @mcp.tool() decorated handler function implementing the core logic of the get_user_summary tool by delegating to the shared DiscourseClient instance.
    @mcp.tool()
    def get_user_summary(
        username: Annotated[
            str,
            Field(description="The user's handle (case-insensitive)"),
        ],
    ) -> UserSummary:
        """
        Fetch a comprehensive summary of a user's profile.
    
        Args:
            username: The user's handle (case-insensitive)
    
        Returns a UserSummary object with:
        - user_id: User ID
        - username: Username
        - stats: UserStats with posts, topics, likes given/received, etc.
        - badges: List of recent Badge objects
        - top_topics: Most successful topics
        - top_replies: Most successful replies
    
        Use this to:
        - Evaluate a user's credibility and experience
        - Find their most valuable contributions
        - Understand their participation level
    
        The summary provides a quick overview without fetching
        individual post histories.
        """
        return get_client().get_user_summary(username)
  • Pydantic BaseModel defining the output schema (UserSummary) returned by the get_user_summary tool, including user details, stats, badges, and top content.
    class UserSummary(BaseModel):
        """Comprehensive user profile summary."""
    
        user_id: int | None = Field(None, description="User ID")
        username: str | None = Field(None, description="Username")
        name: str | None = Field(None, description="Display name")
        created_at: datetime | None = Field(None, description="Account creation date")
        last_seen_at: datetime | None = Field(None, description="Last seen online")
        stats: UserStats | None = Field(None, description="User statistics")
        badges: list[Badge] = Field(default_factory=list, description="Recent badges")
        top_topics: list[Any] = Field(default_factory=list, description="Top topics")
        top_replies: list[Any] = Field(default_factory=list, description="Top replies")
    
        class Config:
            extra = "ignore"
  • Import statement in the server entrypoint that brings the get_user_summary tool (line 35) into scope for registration via FastMCP when main() is run.
    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,
    )
  • Shared get_client() utility function that creates and returns the singleton DiscourseClient instance (with optional auto-login), used by all server tools including get_user_summary.
    def get_client() -> DiscourseClient:
        """Get or create the Discourse client instance."""
        global _client, _login_attempted
    
        if _client is None:
            base_url = os.environ.get("USCARDFORUM_URL", "https://www.uscardforum.com")
            timeout = float(os.environ.get("USCARDFORUM_TIMEOUT", "15.0"))
            _client = DiscourseClient(base_url=base_url, timeout_seconds=timeout)
    
            # Auto-login if credentials are provided
            if not _login_attempted:
                _login_attempted = True
                username = os.environ.get("NITAN_USERNAME")
                password = os.environ.get("NITAN_PASSWORD")
    
                if username and password:
                    try:
                        result = _client.login(username, password)
                        if result.success:
                            print(f"[uscardforum] Auto-login successful as '{result.username}'")
                        elif result.requires_2fa:
                            print(
                                "[uscardforum] Auto-login failed: 2FA required. Use login() tool with second_factor_token."
                            )
                        else:
                            print(
                                f"[uscardforum] Auto-login failed: {result.error or 'Unknown error'}"
                            )
                    except Exception as e:  # pragma: no cover - logging side effect
                        print(f"[uscardforum] Auto-login error: {e}")
    
        return _client
  • UsersAPI.get_user_summary method that performs the actual HTTP request to /u/{username}/summary.json, parses the response, constructs UserStats and Badge objects, and returns the UserSummary.
    def get_user_summary(self, username: str) -> UserSummary:
        """Fetch user profile summary.
    
        Args:
            username: User handle
    
        Returns:
            Comprehensive user summary
        """
        payload = self._get(f"/u/{username}/summary.json")
    
        # Extract user stats from various locations
        user_summary = payload.get("user_summary", {})
        user = payload.get("users", [{}])[0] if payload.get("users") else {}
    
        stats = UserStats(
            likes_given=user_summary.get("likes_given", 0),
            likes_received=user_summary.get("likes_received", 0),
            days_visited=user_summary.get("days_visited", 0),
            post_count=user_summary.get("post_count", 0),
            topic_count=user_summary.get("topic_count", 0),
            posts_read_count=user_summary.get("posts_read_count", 0),
            topics_entered=user_summary.get("topics_entered", 0),
        )
    
        badges = []
        for b in user_summary.get("badges", []):
            badges.append(Badge(
                id=b.get("id", 0),
                badge_id=b.get("badge_id", b.get("id", 0)),
                name=b.get("name", ""),
                description=b.get("description"),
                granted_at=b.get("granted_at"),
            ))
    
        return UserSummary(
            user_id=user.get("id"),
            username=user.get("username", username),
            name=user.get("name"),
            created_at=user.get("created_at"),
            last_seen_at=user.get("last_seen_at"),
            stats=stats,
            badges=badges,
            top_topics=user_summary.get("top_topics", []),
            top_replies=user_summary.get("top_replies", []),
        )
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 explaining what the tool returns (UserSummary object structure) and its behavioral characteristics (provides quick overview, case-insensitive username handling). It doesn't mention rate limits, authentication requirements, or error conditions, keeping it from a perfect score.

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?

Well-structured with clear sections (Args, Returns, Use cases) and efficient sentences. Slightly verbose with the detailed return structure listing that could be inferred from output schema, but overall earns its place with helpful guidance.

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 an output schema (though not shown here, context signals indicate it exists), the description provides excellent contextual completeness by explaining the tool's purpose, usage scenarios, and behavioral characteristics without needing to duplicate return value documentation.

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% with the parameter already documented in the schema. The description repeats the parameter documentation verbatim ('username: The user's handle (case-insensitive)') without adding meaningful semantic context beyond what's in the schema, meeting the baseline for high schema coverage.

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 with specific verb ('Fetch') and resource ('comprehensive summary of a user's profile'), distinguishing it from siblings like get_user_badges or get_user_topics by emphasizing it provides a holistic overview rather than specific components.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('Use this to: Evaluate a user's credibility... Find their most valuable contributions... Understand their participation level') and when not to use it ('without fetching individual post histories'), providing clear alternatives to more granular sibling tools.

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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