Crawlora MCP

sparkfun_search

Read-only

Search public SparkFun product records with q, pagination, and dynamic facets; pass filters as attribute:value using values in the response's filters list. Use sparkfun_product for one item or sparkfun_category for a category grid.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "sparkfun_search"
  }
}

Input Schema

Name	Required	Description
`q`	Yes	Product search query
`page`	No	One-based result page (1-100)
`filter`	No	Repeatable dynamic facet in attribute:value form
`per_page`	No	Products per page (1-24)

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 7, 2026
- addedInput schema / properties / filter / description
```
Added value: +"Repeatable dynamic facet in attribute:value form"
```
- addedInput schema / properties / page / description
```
Added value: +"One-based result page (1-100)"
```
- addedInput schema / properties / per_page / description
```
Added value: +"Products per page (1-24)"
```
- addedInput schema / properties / q / description
```
Added value: +"Product search query"
```
First observedOct 7, 2026

TDQS

A4.4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds a genuinely useful behavioral note that filter values must come from the response's filters list, but says nothing about result volume, rate limits, or ordering. With annotations carrying the safety burden, a 3 is appropriate.

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?

Two sentences, both earning their place, with the core purpose and filter mechanics front-loaded ahead of the sibling routing. No filler.

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?

An output schema exists and schema coverage is full, so return values and pagination bounds need no repetition. Purpose, alternatives, and filter semantics are all covered; only richer behavioral detail (result ordering, volume) is absent, which is a minor gap.

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?

Schema coverage is 100%, so baseline is 3, but the description goes beyond the schema by specifying that filters are passed as attribute:value using values surfaced in the response's filters list, clarifying the otherwise cryptic 'Repeatable dynamic facet' schema text. That is real added meaning for the filter parameter.

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 names a specific verb (Search) and resource (public SparkFun product records) and immediately scopes it against the sibling tools. An agent can tell it apart from sparkfun_product and sparkfun_category without opening any schema.

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?

It explicitly routes the agent: use sparkfun_product for one item and sparkfun_category for a category grid, which implicitly delimits when this search tool is the right choice. This is the same pattern as the high-scoring calibration example.

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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