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mysleekdesigns

CrawlForge MCP Server

by mysleekdesigns
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JavaScript
Remote

extract_metadata

Read-onlyIdempotent

Extract SEO metadata from a webpage, including title, meta description, Open Graph tags, canonical URL, and schema.org data. Optionally filter JSON-LD to specific types.

Instructions

Use this for a page's SEO metadata only: title, meta description, Open Graph tags, canonical URL, schema.org data. Not alongside a scrape of the same URL: scrape formats:["markdown","metadata"] returns both in one fetch. Cost: 1 credit. Example: extract_metadata({url: "https://example.com"})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to extract metadata from
user_agentNoOverride the outbound User-Agent. CrawlForge identifies itself honestly by default; use this only for targets you have your own agreement with.
json_ld_typesNoFilter the returned JSON-LD to nodes of these schema.org types, e.g. ["Product","Offer"]. Subtypes match their parent: "Event" returns MusicEvent, "Offer" returns AggregateOffer, "ItemList" returns BreadcrumbList. Nodes are found at any depth, including inside @graph and nested inside a parent node. When set, json_ld carries only the matching nodes instead of the raw dump, and json_ld_type_counts reports how many matched per requested type. Documented types: ItemList, Product, Offer, Event, JobPosting, RealEstateListing — any other schema.org type is matched exactly.
respect_robotsNoRespect the target site's robots.txt (default: true). Setting this to false is honoured, returns a warning in the response, and is recorded against your API key — it is your decision, not a silent default.

Schema Changelog

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

  1. Changed1 schema field changedv6.0.0
    • removedInput schema / additionalProperties
      Removed value: -false
  2. Changed3 schema fields changedv5.4.0
    • addedInput schema / properties / json_ld_types
      Added value: +{
+  "description": "Filter the returned JSON-LD to nodes of these schema.org types, e.g. [\"Product\",\"Offer\"]. Subtypes match their parent: \"Event\" returns MusicEvent, \"Offer\" returns AggregateOffer, \"ItemList\" returns BreadcrumbList. Nodes are found at any depth, including inside @graph and nested inside a parent node. When set, json_ld carries only the matching nodes instead of the raw dump, and json_ld_type_counts reports how many matched per requested type. Documented types: ItemList, Product, Offer, Event, JobPosting, RealEstateListing — any other schema.org type is matched exactly.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
    • addedInput schema / properties / respect_robots
      Added value: +{
+  "description": "Respect the target site's robots.txt (default: true). Setting this to false is honoured, returns a warning in the response, and is recorded against your API key — it is your decision, not a silent default.",
+  "type": "boolean"
+}
    • addedInput schema / properties / user_agent
      Added value: +{
+  "description": "Override the outbound User-Agent. CrawlForge identifies itself honestly by default; use this only for targets you have your own agreement with.",
+  "type": "string"
+}
  3. Changed1 schema field changedv5.0.4
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  4. First observedv4.10.0

TDQS

A4.2/5.0
Behavior3/5

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

The annotations already declare readOnly, idempotent, and non-destructive behavior, so the safety profile is covered. The description adds the cost detail ('1 credit') and a note about avoiding duplicate scrapes, but it does not disclose behavioral aspects like response shape, robots.txt handling, or user_agent defaults beyond what annotations already imply.

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 compact and front-loaded: the core purpose appears first, followed by the anti-duplication warning, cost, and a usage example. Every sentence earns its place and there is no redundant wording.

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?

Given the tool's moderate complexity and the fully documented input schema, the description covers the essential operational details: purpose, when to avoid it, cost, and an example call. It does omit an explicit description of the response envelope, but the listed metadata fields already hint at the return content, so nothing critical is missing.

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 the schema already documents all four parameters. The description only shows a URL example and does not go beyond the schema's parameter documentation, so it meets the baseline but provides no additional parameter-level meaning.

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 and resource: extracting a page's SEO metadata, then enumerates exactly which fields are included (title, meta description, Open Graph tags, canonical URL, schema.org data). It also distinguishes itself from the scrape tool by explicitly warning against using it alongside a scrape of the same URL.

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 states precisely when to use the tool ('for a page's SEO metadata only') and when not to use it ('Not alongside a scrape of the same URL'). It names the alternative and the exact condition that makes it better: scrape with formats ['markdown','metadata'] returns both in one fetch.

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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