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cfbd-mcp-server

by lenwood

get-advanced-box-score

Retrieve detailed statistical data for college football games from the College Football Data API using a specific game identifier.

Instructions

Note: When using this tool, please explicitly mention that you are retrieving data from the College Football Data API. You must mention "College Football Data API" in every response.

Get advanced box score data for college football games.
        Required: gameId
        Example valid queries:
        - gameId=401403910
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gameIdYes

Implementation Reference

  • Registration of the get-advanced-box-score tool in the @server.list_tools() handler, specifying name, description, and inputSchema generated from getAdvancedBoxScore TypedDict.
    types.Tool(
        name="get-advanced-box-score",
        description=base_description + """Get advanced box score data for college football games.
        Required: gameId
        Example valid queries:
        - gameId=401403910
        """,
        inputSchema=create_tool_schema(getAdvancedBoxScore)
    )
  • Generic tool handler decorated with @server.call_tool(). Maps 'get-advanced-box-score' to getAdvancedBoxScore schema (line 518) for validation and to '/game/box/advanced' endpoint (line 542). Makes authenticated API GET request and returns JSON response as text.
    @server.call_tool()
    async def handle_call_tool(
        name: str,
        arguments: dict[str, Any] | None
    ) -> list[types.TextContent]:
        """Handle tool execution requests."""
        if not arguments:
            raise ValueError("Arguments are required")
    
        # Map tool names to their parameter schemas
        schema_map = {
            "get-games": getGames,
            "get-records": getTeamRecords,
            "get-games-teams": getGamesTeams,
            "get-plays": getPlays,
            "get-drives": getDrives,
            "get-play-stats": getPlayStats,
            "get-rankings": getRankings,
            "get-pregame-win-probability": getMetricsPregameWp,
            "get-advanced-box-score": getAdvancedBoxScore
        }
    
        if name not in schema_map:
            raise ValueError(f"Unknown tool: {name}")
    
        # Validate parameters against schema
        try:
            validated_params = validate_params(arguments, schema_map[name])
        except ValueError as e:
            return [types.TextContent(
                type="text",
                text=f"Validation error: {str(e)}"
            )]
    
        endpoint_map = {
            "get-games": "/games",
            "get-records": "/records",
            "get-games-teams": "/games/teams",
            "get-plays": "/plays",
            "get-drives": "/drives",
            "get-play-stats": "/play/stats",
            "get-rankings": "/rankings",
            "get-pregame-win-probability": "/metrics/wp/pregame",
            "get-advanced-box-score": "/game/box/advanced"
        }
       
        async with await get_api_client() as client:
            try:
                response = await client.get(endpoint_map[name], params=arguments)
                response.raise_for_status()
                data = response.json()
                return [types.TextContent(
                    type="text",
                    text=str(data)
                )]
            except httpx.HTTPStatusError as e:
                if e.response.status_code == 401:
                    return [types.TextContent(
                        type="text",
                        text="401: API authentication failed. Please check your API key."
                    )]
                elif e.response.status_code == 403:
                    return [types.TextContent(
                        type="text",
                        text="403: API access forbidden. Please check your permission."
                    )]
                elif e.response.status_code == 429:
                    return [types.TextContent(
                        type="text",
                        text="429: Rate limit exceeded. Please try again later."
                    )]
                else:
                    return [types.TextContent(
                        type="text",
                        text=f"API Error: {e}"
                    )]
            except httpx.RequestError as e:
                return [types.TextContent(
                    type="text",
                    text=f"Network error: {str(e)}"
                )]
  • TypedDict schemas for tool input parameters (getAdvancedBoxScore: requires gameId) and response (AdvancedBoxScoreResponse: contains teams and players stats). Supporting types like TeamStats, PlayerStats defined earlier in file.
    class getAdvancedBoxScore(TypedDict): # /game/box/advanced endpoint
        gameId: int
    
    class AdvancedBoxScoreResponse(TypedDict): # /game/box/advanced endpoint
        teams: TeamStats
        players: PlayerStats
  • validate_params helper function used by handler to validate tool arguments against the TypedDict schema (e.g., getAdvancedBoxScore). Handles optionals, required fields, type checks, and valid classifications.
    def validate_params(params: dict, schema_class: Type[TypedDict]) -> dict:
        """Validate parameters against a TypedDict schema."""
        try:
            # Get the annotations from the schema class
            expected_types = schema_class.__annotations__
            validated_params = {}
    
            # Validate each parameter
            for key, value in params.items():
                if key not in expected_types:
                    raise ValueError(f"Unexpected parameter: {key}")
    
                expected_type = expected_types[key]
    
                # Special handling for classification parameter
                if key == "classification" and value is not None:
                    value = value.lower()
                    if value not in VALID_DIVISIONS:
                        raise ValueError(f"Invalid Classification: Must be one of: {', '.join(VALID_DIVISIONS)}")
    
                # Handle Optional types
                if hasattr(expected_type, "__origin__") and expected_type.__origin__ is Union:
                    if type(None) in expected_type.__args__:
                        # Parameter is optional
                        if value is not None:
                            # Validate against the non-None type
                            non_none_type = next(t for t in expected_type.__args__ if t != type(None))
                            # Handle primitive types
                            if non_none_type in (str, int, float, bool):
                                if not isinstance(value, non_none_type):
                                    raise ValueError(f"Parameter {key} must be of type {non_none_type.__name__}")
                            validated_params[key] = value
                        else:
                            validated_params[key] = None
                else:
                    # Parameter is required
                    if not isinstance(value, expected_type):
                        raise ValueError(f"Parameter {key} must be of type {expected_type.__name__}")
                    validated_params[key] = value
    
            # Check for required parameters
            for param, param_type in expected_types.items():
                is_optional = (hasattr(param_type, "__origin__") and 
                             param_type.__origin__ is Union and 
                             type(None) in param_type.__args__)
                if not is_optional and param not in params:
                    raise ValueError(f"Missing required parameter: {param}")
    
            return validated_params
        
        except Exception as e:
            raise ValueError(f"Parameter validation failed: {str(e)}")
  • create_tool_schema helper converts TypedDict (e.g., getAdvancedBoxScore) to JSON Schema object used for tool's inputSchema in registration.
    def create_tool_schema(params_type: Type) -> dict:
        """Create a tool schema from a TypedDict."""
        return typed_dict_to_json_schema(params_type)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions a mandatory attribution requirement, which is useful context, but fails to describe other key behaviors such as whether this is a read-only operation, potential rate limits, error handling, or the format of returned data. This leaves significant gaps for an agent to understand how to use it effectively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, but it includes an attribution note that is more of a usage constraint than part of the tool's functional description. The example is helpful but could be integrated more smoothly. Overall, it's moderately concise but has some structural inefficiencies.

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

Completeness2/5

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

Given the complexity of retrieving sports data, no annotations, no output schema, and poor schema coverage, the description is incomplete. It lacks details on authentication, data format, error cases, and how this tool differs from siblings. The mandatory attribution note adds some context but doesn't compensate for the overall gaps.

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

Parameters2/5

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

The schema description coverage is 0%, meaning the input schema provides no useful parameter documentation. The description adds minimal semantics by stating 'Required: gameId' and giving an example, but it doesn't explain what a gameId is, how to obtain it, or its valid range. With one parameter and no schema help, this is insufficient compensation.

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

Purpose4/5

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

The description clearly states the tool's purpose as 'Get advanced box score data for college football games,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate this tool from sibling tools like 'get-games' or 'get-plays,' which might also retrieve game-related data, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'get-games' or 'get-plays.' It includes a mandatory attribution requirement ('College Football Data API') but this is not usage guidance. Without any context on when this tool is appropriate, the score is low.

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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