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guillochon

mlb-api-mcp

get_mlb_awards

Retrieve MLB award recipients by specifying an award ID to access baseball award data through the MLB API MCP server.

Instructions

Get award recipients for a specific award.

Args: award_id (int): Award ID.

Returns: dict: Award recipients.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
award_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function for the 'get_mlb_awards' tool. It is decorated with @mcp.tool(), which registers it with the MCP server. The function fetches award data using the mlbstatsapi library and handles errors.
    @mcp.tool()
    def get_mlb_awards(award_id: int) -> dict:
        """
        Get award recipients for a specific award.
    
        Args:
            award_id (int): Award ID.
    
        Returns:
            dict: Award recipients.
        """
        try:
            awards = mlb.get_awards(award_id)
            return {"awards": awards}
        except Exception as e:
            return {"error": str(e)}
  • main.py:22-23 (registration)
    The call to setup_mlb_tools(mcp) in main.py, which executes the function definitions and @mcp.tool() decorators, thereby registering the 'get_mlb_awards' tool (along with other MLB tools) to the FastMCP server instance.
    setup_mlb_tools(mcp)
    setup_generic_tools(mcp)
  • The input schema (award_id: int) and output description defined in the tool's docstring, used by MCP for validation.
    Args:
        award_id (int): Award ID.
    
    Returns:
        dict: Award recipients.
    """
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. It states it's a read operation ('Get'), but lacks details on permissions, rate limits, error handling, or data format beyond 'dict.' For a tool with no annotations, this is insufficient behavioral disclosure.

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 appropriately sized and front-loaded with the main purpose. The 'Args' and 'Returns' sections are structured but could be more integrated. No wasted sentences, though it could be slightly more polished.

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

Completeness3/5

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

Given 1 parameter, 0% schema coverage, no annotations, and an output schema (implied by 'Returns: dict'), the description is minimally adequate. It covers the basic purpose and parameter, but lacks context on usage, behavioral traits, or deeper semantics, making it incomplete for optimal agent use.

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 0%, so the description must compensate. It adds minimal semantics: 'award_id (int): Award ID.' This clarifies the parameter type and purpose slightly beyond the schema's 'type: integer,' but doesn't explain valid ranges, examples, or how to obtain award IDs. Baseline is 3 due to low coverage and partial 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: 'Get award recipients for a specific award.' It specifies the verb ('Get') and resource ('award recipients'), distinguishing it from siblings like get_mlb_players or get_mlb_teams. However, it doesn't explicitly differentiate from other award-related tools (none in siblings), so it's not a perfect 5.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, context, or exclusions, such as whether it's for current or historical awards, or if there are other tools for award lists. It's a basic statement without usage context.

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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