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brightdata

Bright Data MCP

Official
by brightdata

get_scraper_details

Read-only

Retrieve a scraper method's description, input fields, sample input, and key output fields before running it, so you can build valid scraper inputs.

Instructions

Show the scraper description, input fields, example input and main output fields for one method. Call before run_scraper and build the input from sample_input or input_fields. Records may contain more fields than output_fields lists.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodYesOne of the scraper collection_methods, exactly as listed (some names are misspelled on purpose)
dataset_idYesdataset_id from search_scrapers

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds a genuine behavioral caveat: 'Records may contain more fields than output_fields lists,' which warns the agent not to treat output_fields as exhaustive. This is useful context beyond the annotations.

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 tight sentences, front-loaded with what is returned, then workflow placement, then the output caveat. No filler; every sentence earns its place.

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?

There is no output schema, but the description compensates by naming what the response contains (description, input fields, sample_input, output_fields) and noting the records-vs-output_fields gap. Coverage is strong for a simple two-required-param read tool, though it could note anything about error behavior for an unknown method.

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 both 'method' and 'dataset_id' are already documented, including the deliberate-misspelling note and the search_scrapers origin. The description adds no syntax or format detail beyond the schema, so the baseline 3 is appropriate.

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 gives a specific verb ('Show') and enumerates the exact resource returned (scraper description, input fields, example input, main output fields) scoped to 'one method'. This clearly distinguishes it from siblings like search_scrapers (discovery) and run_scraper (execution).

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?

'Call before run_scraper and build the input from sample_input or input_fields' explicitly places the tool in the workflow and names the sibling it precedes, with the condition for invoking it. An agent knows exactly when to reach for this versus run_scraper.

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