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Public APIs MCP

by zazencodes

get_public_api_details

Retrieve comprehensive details for any API in the catalog using its unique identifier.

Instructions

Get detailed information about a specific API by its unique public-apis-mcp server ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
apiYesAPI display name
api_linkYes
descriptionYes
authNo
httpsNo
corsNo
categoryNo

Implementation Reference

  • The tool handler function 'get_public_api_details' that executes the tool logic: takes an API id string, loads the catalog, looks up the item by id, and returns the ApiItem or raises ValueError if not found.
    @mcp.tool
    def get_public_api_details(id: str) -> ApiItem:
        """Get detailed information about a specific API by its
        unique public-apis-mcp server ID
        """
        items, by_id = load_catalog_indexed()
        item = by_id.get(id)
        if not item:
            raise ValueError(f"API id not found: {id}")
        return item
  • The ApiItem Pydantic model used as the return type / output schema for get_public_api_details.
    class ApiItem(BaseModel):
        id: str
        api: str = Field(description="API display name")
        api_link: str
        description: str
        auth: str | None = None
        https: str | bool | None = None
        cors: str | None = None
        category: str | None = None
  • The tool is registered via the @mcp.tool decorator on the get_public_api_details function inside register_tools() which receives the FastMCP instance.
    @mcp.tool
    def get_public_api_details(id: str) -> ApiItem:
        """Get detailed information about a specific API by its
        unique public-apis-mcp server ID
        """
        items, by_id = load_catalog_indexed()
        item = by_id.get(id)
        if not item:
            raise ValueError(f"API id not found: {id}")
        return item
  • The helper function 'load_catalog_indexed' that loads and indexes the catalog, used by the tool to look up an API by id.
    def load_catalog_indexed() -> tuple[list[ApiItem], dict[str, ApiItem]]:
        items = load_catalog()
        index = {i.id: i for i in items}
        return items, index
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states it returns 'detailed information' without specifying any side effects, auth requirements, rate limits, or output format beyond the schema. This leaves significant gaps for a tool with no annotations.

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 a single, front-loaded sentence of 12 words. It contains no fluff and conveys the essential purpose efficiently.

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 the tool's low complexity (1 parameter, presence of output schema) and the absence of annotations, the description adequately covers the purpose and parameter meaning. It does not discuss edge cases or error scenarios, but these are likely not critical for a straightforward get operation.

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

Parameters4/5

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

The only parameter 'id' has 0% schema description coverage, but the description clarifies that the ID is the 'unique public-apis-mcp server ID', adding meaning beyond the schema field title 'Id'.

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 action ('Get detailed information'), the resource ('specific API'), and the identifier ('unique public-apis-mcp server ID'). It distinguishes from the sibling tool 'search_public_apis' by focusing on a single API retrieval.

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 implies when to use this tool: when you have a specific server ID and need detailed info. It does not explicitly mention when not to use or mention alternatives, but the context is clear enough.

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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