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Apex Flow 3D Scraper

Apex Flow 3D Scraper

Official
by Apexflowlabsllc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

scrape_page

Fetch public web pages and source receipts, then optionally extract named CSS fields or split text into chunks for downstream processing.

Instructions

Fetch public content and its source receipt. Optionally extract named CSS fields and split text into chunks. Costs 1 or 3 credits.

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": {
      "url": "<url>"
    },
    "name": "scrape_page"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYes
chunksNo
fieldsNo
renderNoauto

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden, and it does contribute real context: content is public, the call is metered, and there are two credit tiers. It omits what the 'source receipt' contains, how credit cost maps to the render/chunks options, whether failed scrapes still burn credits, and any rate limits or failure modes.

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?

Three short sentences, front-loaded with the core action, then the optional behaviors, then the cost. No filler and no repetition of the schema.

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

Completeness2/5

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

A four-parameter scraping tool with no annotations, no output schema, and 0% schema coverage needs the description to do heavy lifting, and it does not. Render semantics, the return shape of the 'source receipt', and which conditions cause the 1- versus 3-credit charge are all missing, leaving the agent to guess on a tool that has a real cost per call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain all four parameters and does so only partially: 'named CSS fields' maps loosely to fields and 'split text into chunks' to chunks, but url and the render enum (auto/always/never) are entirely unexplained. The agent gets no idea what triggers browser rendering or what the chunk count means.

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

Purpose4/5

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

States a specific verb and resource: fetching public page content plus its 'source receipt', with optional CSS field extraction and chunking. That is far more informative than the bare name 'scrape_page'. It does not, however, distinguish this from the sibling scrape_batch (single page vs. many), so an agent must infer the boundary from the name alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The word 'public' and the optional field/chunk flags imply when the extra features are relevant, so usage is partially conveyed. There is no explicit when-to-use versus scrape_batch, no statement about prerequisites, and no guidance on when the credit costlier mode is worth paying for.

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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