Diogenes Web Extraction, Readability & Markdown Engine MCP

OpenGraph, Twitter Cards & JSON-LD Microdata Extractor

extract_structured_metadata

Read-onlyIdempotent

Extract OpenGraph, Twitter Card, canonical URLs, and Schema.org JSON-LD metadata from HTML to index social cards, author identity, breadcrumbs, and rich snippets for AI search agents.

Instructions

Extracts OpenGraph tags, Twitter Card metadata, canonical URLs, and Schema.org JSON-LD microdata scripts from HTML. Use when indexing social share cards, author identity, breadcrumbs, and rich snippet schemas for AI search agents; for scanning page hyperlinks and outbound references, use extract_page_hyperlinks instead. Stateless read-only edge call (max 32 KB, 60 RPM): accepts 'html_content' ('metadata_targets' defaults to 'all_protocols'), supports '?demo=true' or L402 (10 sats), and returns HTTP 400 if invalid.

Input Schema

Name	Required	Description
`html_content`	Yes	Source HTML string containing head tags, OpenGraph meta properties, or JSON-LD scripts.
`include_favicons`	No	Whether to extract favicon links and Apple Touch icon references.
`metadata_targets`	No	Target metadata protocol filter: all protocols, OpenGraph and Twitter, or Schema.org JSON-LD.

Output Schema

Name	Required	Description
`open_graph`	Yes	Structured OpenGraph properties including og:title, og:image, and og:description.
`twitter_card`	Yes	Twitter Card metadata including twitter:card, twitter:creator, and twitter:image.
`canonical_url`	Yes	Canonical canonical link target or empty string if unspecified.
`json_ld_schemas`	Yes	Parsed Schema.org JSON-LD structured data objects.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 26, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already cover read-only/idempotent/non-destructive, but the description adds genuinely new operational context: stateless edge call, 32 KB payload cap, 60 RPM rate limit, and auth via '?demo=true' or L402 (10 sats). HTTP 400 error behavior is also disclosed. It stops short of describing the return payload shape, but with an output schema present that is acceptable.

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?

Three front-loaded sentences, no filler, with purpose first and the routing alternative immediately after. The final sentence is dense with limits, defaults, and pricing, but every clause carries information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only extraction tool with an output schema, the description supplies everything else that matters: size limit, rate limit, auth/payment path, invalid-input behavior, and parameter default. No operational gap remains for an agent to call it 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 the baseline is 3, but the description adds value the schema does not: it states that 'metadata_targets' defaults to 'all_protocols', which is not encoded as a default in the schema. It does not explain include_favicons, but that parameter is fully documented in 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?

States a specific verb and enumerates the exact resources extracted (OpenGraph, Twitter Cards, canonical URLs, JSON-LD), and explicitly names the sibling extract_page_hyperlinks as the different tool. An agent can distinguish this from extract_structured_json_entities or extract_page_hyperlinks without opening a 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?

Provides explicit when-to-use triggers (social share cards, author identity, breadcrumbs, rich snippets) plus an explicit when-not with the alternative tool named ('for scanning page hyperlinks ... use extract_page_hyperlinks instead'). Routing is unambiguous.

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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