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AI Makerspace MCP Demo Server

by lalrow

number_fact

Retrieve interesting facts about numbers or dates using the NumbersAPI. Enter a number or date to get a factual response.

Instructions

Get an interesting fact about a number or date using NumbersAPI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • server.py:29-40 (handler)
    This is the handler function for the 'number_fact' tool. It fetches an interesting fact about a number or date from numbersapi.com using an HTTP request. The @mcp.tool() decorator registers it with the MCP server.
    def number_fact(query: str) -> str:
        """Get an interesting fact about a number or date using NumbersAPI."""
        try:
            # You can pass things like "42", "math/42", or "date/6/14"
            url = f"http://numbersapi.com/{query}"
            response = requests.get(url)
            if response.status_code == 200:
                return response.text
            else:
                return f"⚠️ API error: {response.status_code}"
        except Exception as e:
            return f"❌ Something went wrong: {e}"
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 states the tool retrieves facts but doesn't describe traits like rate limits, error handling, response format, or whether it's read-only. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero waste, making it easy to parse quickly.

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 the tool's low complexity (1 parameter) and the presence of an output schema, the description is minimally adequate. However, with no annotations and incomplete parameter semantics, it lacks details on usage, behavior, and input specifics. The output schema may cover return values, but the description doesn't provide enough context for effective tool selection and invocation.

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 input schema has 1 parameter with 0% description coverage, and the tool description adds no information about the 'query' parameter. It doesn't explain what the query should contain (e.g., format for numbers or dates), examples, or constraints. With low schema coverage, the description fails to compensate, leaving the parameter undocumented.

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 an interesting fact about a number or date using NumbersAPI.' It specifies the action ('Get'), resource ('interesting fact'), and scope ('number or date'), though it doesn't explicitly differentiate from siblings like 'animal_fact' or 'science_term' beyond the domain. This is clear but lacks sibling differentiation.

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. It doesn't mention siblings like 'animal_fact' or 'web_search', nor does it specify contexts or exclusions for number/date facts. Usage is implied by the purpose but not explicitly stated.

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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