BuiltWith

Ask API

ask-api

Ask API lookup for natural language website list queries. OpenAI requests are served as preview results and do not commit full reports.

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": {
      "query": "<query>"
    },
    "name": "ask-api"
  }
}

Input Schema

Name	Required	Description
`meta`	No	Set to true to include metadata in the results
`query`	Yes	The natural language query (e.g. 'Magento websites in Spain')
`commit`	No	Ignored for OpenAI/ChatGPT requests; preview mode is always used there
`nextOffset`	No	Pagination offset from the previous response's NextOffset

Output Schema

Name	Required	Description	Default
`count`	Yes
`query`	Yes
`sites`	Yes
`committed`	Yes
`nextOffset`	No
`openAiPreview`	Yes
`requestedCommit`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

C2.9/5.0

Behavior3/5

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

Annotations declare readOnlyHint=false, destructiveHint=false, and openWorldHint=false, so the description's added job is to explain the mutation semantics. It does this partly by noting OpenAI requests are served as preview results and do not commit full reports, which clarifies the commit behavior. It stops short of explaining what a non-preview commit actually does or what state changes, leaving a gap for a non-read-only tool.

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?

Two compact sentences, front-loading the core purpose before the OpenAI preview caveat. Nothing is padded, though the first sentence spends words on "Ask API lookup" that partially restate the tool name.

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?

An output schema exists, so return values need not be explained, and the preview caveat covers the key operational surprise. Still, for a 4-parameter tool with numerous similar siblings, the description lacks routing guidance and any statement of limits or result characteristics, leaving it only minimally sufficient.

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 100%, so baseline is 3. The description's note about preview/commit behavior loosely reinforces the `commit` parameter but adds no syntax, defaults, or interaction details (e.g., how nextOffset interacts with preview results) beyond what the schema already states.

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

Purpose3/5

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

"Ask API lookup for natural language website list queries" does convey the resource type (website lists) and input modality (natural language), which is more than a pure restatement of the name. However, "Ask API lookup" echoes the tool name, and nothing distinguishes this from close siblings like ask-api-json or x402-ask-api, so an agent cannot route confidently on purpose alone.

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 when-to-use or when-not-to-use guidance is given relative to the many sibling query tools. The only conditional statement concerns OpenAI request handling (preview mode), not tool selection, so the agent is left to infer applicability.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All BuiltWith tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.