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webbersites-x402-data-api

by io.github.webberdesign

post_extract_custom

CUSTOM EXTRACTION — POST {content, schema} and get structured JSON back. Define fields as {"company":"string","total":"number","due_date":"date"} (types or plain-language descriptions) and the engine pulls them from any unstructured text: emails, invoices, job posts, resumes, chat logs. Missing fields return null — never invented. Content up to 16,000 chars, 40 fields max. Parsing a PDF/DOCX/CSV by URL first? GET /api/extract ($0.02). ($0.01 per call, paid via x402)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
schemaYesFields to extract: {name: type-or-description}. Types: string, number, boolean, date, string[], number[] — or a plain-language description ('the total in USD')
contentYesThe unstructured text to extract from, up to 16,000 characters
instructionsNoOptional extra guidance, e.g. 'dates are DD/MM/YYYY in this document'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoone key per schema field; null where the content had no answer
modelNo
usageNo
missingNonames of fields that came back null

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations provide openWorldHint but no destructive or idempotent hints. The description adds important behavioral detail: missing fields return null (never invented), and content limits. This goes beyond annotations and helps the agent understand edge cases.

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 a single compact paragraph covering purpose, usage, behavior, limits, and alternatives. It is front-loaded with the key action. While dense, every sentence adds value, so it earns a 4.

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?

For a tool of this complexity (custom extraction with schema), the description covers input constraints, behavior on missing fields, and cost. Although the output schema is not shown, it is referenced. The description is complete enough for an agent to use the tool correctly.

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. The description adds value by explaining that schema values can be types or plain-language descriptions (with example), and that instructions are optional extra guidance, enhancing understanding beyond the schema.

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 tool performs custom extraction: POST unstructured content and a schema, return structured JSON. It specifies use cases (emails, invoices, job posts, etc.) and distinguishes from sibling GET /api/extract tool by mentioning URL-based parsing alternatives.

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 provides clear context on when to use the tool: for extracting fields from unstructured text. It mentions limits (16,000 chars, 40 fields) and cost, and references the GET alternative for file parsing, helping the agent decide between tools. However, it does not explicitly state when not to use this tool.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but the SEO-related tools (head_check, full_audit, site_audit, etc.) overlap in scope, potentially causing confusion despite clear descriptions.

Naming Consistency5/5

Tool names consistently follow a get_/post_/delete_ verb pattern with descriptive noun phrases (e.g., get_seo_head_check, post_store_collection), with no mixing of naming conventions.

Tool Count2/5

With 46 tools covering a wide breadth of domains (SEO, accessibility, music, crypto, linting, etc.), the count is excessive for a single server, feeling unfocused and heavy.

Completeness4/5

The tool set covers most core operations for each sub-domain, but minor gaps exist (e.g., missing update for datastore, limited music operations).

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