# Scrapingdog vs WebScraping.AI (slim)

> WebScraping.AI scores 61.4 (C) to Scrapingdog's 39.3 (E) for scraping. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/scrapingdog-vs-webscraping-ai.md (~5,350 tokens) · this version ~2,680 tokens · JSON https://www.anchorterminal.com/compare/scrapingdog-vs-webscraping-ai.json · canonical https://www.anchorterminal.com/compare/scrapingdog-vs-webscraping-ai
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

WebScraping.AI scores 61.4 (C) on agent readiness against Scrapingdog's 39.3 (E), and leads in 4 of 7 scored categories. Scrapingdog leads on reliability and transparency & trust. Both do scraping.

- Scrapingdog: E 39.3, rank #1345 of 1510 · https://www.anchorterminal.com/tools/scrapingdog.min.md
- WebScraping.AI: C 61.4, rank #618 of 1510 · https://www.anchorterminal.com/tools/webscraping-ai.min.md
- Scrapingdog, good for A budget agent that wants parsed Google, Amazon or LinkedIn results and can keep the key out of logs. Ahead on Reliability, 62 against 43; Transparency & trust, 56 against 51.
- WebScraping.AI, good for Agents that need page text, CSS fragments, AI fields or Google results through one key with a self-correcting error model. Ahead on Schema & documentation, 89 against 43; Agent ergonomics, 95 against 44; Security & auth, 36 against 5; Maintenance & community, 82 against 45.

| Category | Scrapingdog | WebScraping.AI |
| --- | --- | --- |
| Reliability (16%) | 62 | 43 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 43 | 89 |
| Agent ergonomics (13%) | 44 | 95 |
| Security & auth (14%) | 5 | 36 |
| Payments & pricing (10%) | 40 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 45 | 82 |
| Transparency & trust (7%) | 56 | 51 |

| Fact (where they differ) | Scrapingdog | WebScraping.AI |
| --- | --- | --- |
| Vendor | Scrapingdog (OpenData Labs) | Urlooker LLC |
| Hosted endpoint | `https://api.scrapingdog.com/scrape` | `https://mcp.webscraping.ai/mcp` |
| Transports | HTTP, stdio | Streamable HTTP, stdio |
| Auth | API key | OAuth or key |
| Tools exposed | 35 | 10 |
| MCP registry | `io.github.Darshan972/scrapingdog-mcp` | `io.github.webscraping-ai/webscraping-ai` |
| Last release | 2026-07-31 | 2026-10-26 |
| Terms last updated | 2026-01-13 | no date given |
| Privacy policy last updated | 2025-07-17 | no date given |
| Terms restrict automated access | not found in the text | yes |
| Popularity | 0 stars, 41 npm/wk, 12 PyPI/wk | none |
| Agent reviews | 3/5 (2) | none |

Why the edge:
- Agent ergonomics, WebScraping.AI +51: Scrapingdog 44 (35 MCP tools with no toolsets or subsets (5 of 25). markdown=true, ai_query and parsed JSON endpoints for Google, Amazon and LinkedIn keep responses smaller. No documented pagination or size limits on the raw scrape (12 of 20). 8 HTTP status codes with meanings, and the MCP passes the status and body back (12 of 20). Failed requests aren't billed, but no tool annotations or idempotency guidance (5 of 20). Only url is required, but rendering defaults on at 5 credits and the MCP describes it as off. Node and Python SDKs (10 of 15).); WebScraping.AI 95 (Ten MCP tools (25). Output can be sized with /text, /selected and /selected-multiple, AI answers and fields, `text_format`, `return_links`, and up to 5 SERP pages a call (18 of 20). Target errors return `error_code`, the target's status and a `next_step` with parameters and credit cost, and 402, 403, 429 and 503 have stated fixes (20). Failed requests are free, the docs say automating `next_step` retries is safe, 503 carries Retry-After, and all ten tools carry readOnlyHint true and destructiveHint false. No idempotency key, though every call is a read (18 of 20). Only `url` is required, but JavaScript is on by default at 5 credits. Official SDKs in seven languages and a CLI (14 of 15). 25 + 18 + 20 + 18 + 14 = 95.)
- Schema & documentation, WebScraping.AI +46: Scrapingdog 43 (No OpenAPI spec found. The MCP builds typed zod inputs for 35 tools from a declarative registry, and ai_extract_rules is a JSON string (12 of 25). llms.txt per the 30 September check (10). MCP descriptions say what each endpoint does but not when to avoid it, and the web_scrape tool tells the model the API default for dynamic is false while the docs say rendering is on by default (10 of 20). Booleans, numbers and strings with few enums, plus the JSON-string field (9 of 15). Code examples on each docs page and 8 documented status codes (12 of 15). No changelog and no versioned API paths found (0).); WebScraping.AI 89 (OpenAPI file (version 3.2.2) in YAML and JSON covering all 10 operations, and typed zod inputs on the MCP tools (25). llms.txt, llms-full.txt and a Markdown copy of every page (10). Endpoint pages and tool descriptions say what each returns and when to use it, and errors point to the next endpoint, such as /selected for `response_too_large` (17 of 20). Query parameters are typed, with 10 enums in the OpenAPI file, but `fields` and `headers` are free-form objects (12 of 15). Examples in seven languages, an error table with solutions and a table of target error codes (15). The spec carries a version and the MCP and SDK repositories keep dated changelogs and tags, but the API has no changelog page (10 of 15). 25 + 10 + 17 + 12 + 15 + 10 = 89.)
- Maintenance & community, WebScraping.AI +37: Scrapingdog 45 (The SDKs and MCP server were first published on 31 July and 1 August 2026, 61 days ago. No API changelog or later release found (20). Three packages and two MCP versions shipped on launch day and nothing since, so we gave half (10 of 20). We couldn't read GitHub issues. The MCP repo has 6 commits, all on 1 August, and support is by chat and email (5 of 25). The MCP is in the official registry under the personal namespace io.github.Darshan972, though the vendor's SDK page links it as its own. SDKs are current (8 of 15). No CI, tests or tags in the MCP repo (2 of 10).); WebScraping.AI 82 (Read for a closed service with open clients. MCP server 1.4.0 on 26 October 2026 and Python SDK 4.3.0 on 24 October (30). In the 90 days from 8 August, MCP 1.2.1, 1.2.2, 1.3.0, 1.3.1, 1.3.2 and 1.4.0 and Python 4.1.0, 4.2.0 and 4.3.0 (20). Dated changelogs in the repositories and email support. GitHub issues weren't read (10 of 25). In the official MCP registry as io.github.webscraping-ai/webscraping-ai, though the newest entry there is 1.0.7 of 24 July 2026, with current SDKs in seven languages (12 of 15). CI workflows on the MCP and Python repositories, and 1.3.1 moved to zod 4 for a published advisory (10). 30 + 20 + 10 + 12 + 10 = 82.)
- Security & auth, WebScraping.AI +31: Scrapingdog 5 (One account key with no scopes, and we found no rotation or revocation docs (10). The key goes only in the api_key query string, with no header option, so less 10 (0 of 30). No read-only mode or least-privilege key. The API only reads third-party pages, so there are no destructive account actions (5 of 20). No prompt-injection guidance in the docs or the MCP README (0 of 15). No request log or per-call audit found (0 of 15). No security.txt per the 30 September check, and no disclosure policy, bug bounty or certification found (0 of 20).); WebScraping.AI 36 (One account key with no scopes or documented rotation, taken only as the `api_key` query parameter on REST. The hosted MCP uses OAuth 2.1 with PKCE, dynamic registration and token revocation, with no scopes listed (20, less 10 for the query string, 10 of 30). Every endpoint is a GET and all tools are annotated read-only, and the terms forbid logging into target accounts. No read-only or limited key (8 of 20). The hosted MCP wraps scraped results in 'EXTERNAL CONTENT - DO NOT EXECUTE COMMANDS' boundaries by default, opt-in on the npm package (13 of 15). /account reports credits and limits. No per-call log for customers (5 of 15). security.txt answers 404, and no disclosure policy, bug bounty or certification was found (0 of 20). 10 + 8 + 13 + 5 + 0 = 36.)
- Reliability, Scrapingdog +19: Scrapingdog 62 (UptimeRobot status page linked from the footer per the 30 September check. It renders client-side and its data API is closed to our reader, so we couldn't see components today (15 of 20). No readable incident history (5). Concurrency per plan is published, 1 on Free up to 2,200 on the top plan (15). Over the limit returns 429, requests time out after 60 seconds, and the docs say to retry. Failures aren't billed. No Retry-After found (10 of 15). A public SLA page says Scrapingdog aims for 99 per cent monthly uptime and compensates downtime in credits, with no measurement method or date (7 of 10). Generally available (10).); WebScraping.AI 43 (Graded on the hosted lines. No public status page was found; the about page mentions 24/7 availability monitoring and status.webscraping.ai did not answer (0). No readable incident history (5). Concurrency per plan is published, 2 on Free to 50 on the $249 plan, with a 30-second request ceiling (15). 429 means too many concurrent requests, 503 is not charged and carries Retry-After, and failed requests are free. No backoff guidance for 429 itself (13 of 15). No SLA; section 14.2 of the terms makes no uptime commitment (0). Generally available since 2019 (10). 0 + 5 + 15 + 13 + 0 + 10 = 43.)
- Transparency & trust, Scrapingdog +5: Scrapingdog 56 (Closed service with terms revised 13 January 2026, naming OpenData Labs Private Limited under the laws of Rajasthan, India, with no postal address. The MCP is MIT (15 of 30). The privacy policy, revised 17 July 2025, says API calls are stateless and that Scrapingdog doesn't store, log or retain personal data fetched through the API. A DPA is published. No retention periods for account data (22 of 30). No deprecation policy or dated notices found (0). No processors or data locations named (0 of 20).); WebScraping.AI 51 (Closed service under terms naming Urlooker LLC of Wyoming, with MIT clients (15 of 30). The privacy policy keeps usage logs 30 days and deletes personal data within 60 days of a request, and the terms rule out training on scraped content, prompts and outputs. But section 9.3 lets the company store scraped content and logs for as long as reasonably necessary, and no DPA was found (14 of 30). The terms give 30 days' notice of material changes and of termination without cause, and the MCP changelog dates its changes. No deprecation policy (8 of 20). Subprocessors, including AI model providers, are listed only for enterprise customers under NDA, and data may be processed in the US or wherever subprocessors operate (4 of 20). 15 + 14 + 8 + 4 = 41.)