ScrapeAPI MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| SCRAPEAPI_KEY | Yes | Your ScrapeAPI key | |
| SCRAPEAPI_BASE_URL | No | Override API base URL |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| scrape_urlA | Scrape any public URL and return structured data: text, links, images, and metadata. Automatically detects whether JavaScript rendering is needed. Use this when you need to read the content of a webpage. |
| scrape_multipleB | Scrape multiple URLs in parallel and return results for each. Use when you need to compare or aggregate data from several pages. |
| extract_structuredA | Scrape a URL and extract specific fields using CSS selectors. Use when you need structured data from a known page layout (e.g. product price, article title, table data). |
| take_screenshotA | Take a full-page screenshot of a URL and return it as a base64-encoded PNG. Use for visual verification, capturing charts, or archiving page appearances. |
| check_creditsA | Check the remaining scrape credits on the current API key. Use before running large scraping jobs to confirm sufficient balance. |
| list_datasetsA | List all available pre-built datasets. Use when the user wants ready-made data without scraping (jobs, real estate, prices, VC funding, etc.) |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 6 tools
Each tool targets a distinct function: account credits, general scraping, structured extraction, bulk scraping, pre-built datasets, and screenshots. No overlapping purposes.
All tools use consistent snake_case with verb_noun pattern (check_credits, extract_structured, list_datasets, etc.), making them predictable.
Six tools cover the essential capabilities of a scraping API without being excessive. The scope is well-defined and each tool earns its place.
The tool set covers core scraping workflows (single, multiple, structured, screenshots, credit checks, and pre-built datasets). Minor gaps like dataset management exist but don't hinder typical use.