Loading ToolBench
A Model Context Protocol server that provides web crawling and content extraction capabilities using the crawl4ai library, with support for structured data extraction, file processing, YouTube transcripts, and Google search.
The server defines 7 tools with reasonable complexity and mostly complete schemas. However, there are significant gaps in output schema documentation, parameter consistency issues, and missing error handling guidance. Tool naming is mostly verb-noun consistent (crawl_url, extract_*, search_*, process_file), which is good. Descriptions are present but often generic or lack actionable context. Parameter descriptions exist but vary in quality. The crawl_url tool has extensive parameter coverage but lacks clear guidance on mutual exclusivity and expected outputs. No output schemas are documented for any tool, forcing LLMs to guess response structure. Error handling is absent, no guidance on retries, failure modes, or recovery paths.
Crawl a URL and extract content with support for CSS/XPath selectors, screenshots, markdown generation, deep crawling, content filtering, and JavaScript execution
Extract structured data from a URL using CSS selectors or LLM-based extraction with custom JSON schema
Extract transcript from a YouTube video with language preference, optional translation, timestamps, and video metadata
Extract transcripts from multiple YouTube videos in batch with concurrent processing
Process files from URLs including PDF, Office documents (Word, Excel, PowerPoint), and ZIP archives, extracting text content and metadata
Perform Google search with configurable language, region, result count, and optional content filtering
No output schemas documented for any tool. LLMs cannot plan downstream calls or extract returned fields without knowing the response structure. This violates the tool pattern requirement that output schemas be explicit.
crawl_url has 25 parameters with complex interdependencies (css_selector vs xpath, content_filter types, chunking strategies) but no documentation of mutual exclusivity, required parameter combinations, or which parameters apply in which contexts. LLMs will pass invalid combinations.
No error handling guidance. Tools do not document what errors are retryable, what indicates user input is needed, or what recovery steps an LLM should take. Pattern:recovery-guide is absent.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 49 | <=2025-11-25 | v2 |
| 2026-03-09 | F | 39 | 2024-11-05+ | v1 |
Perform multiple Google searches in batch with concurrent processing
extract_structured_data accepts free-form 'schema' (object type with no constraints) and 'extraction_type' as a free string instead of enum. This invites hallucinated extraction types ('semantic', 'regex', 'xpath-css-hybrid') that the server may not support.
crawl_url parameter descriptions lack actionable format hints. E.g., 'timeout' says 'Request timeout in seconds' but does not state range (suggested 5-300). 'overlap_rate' says '0.0-1.0' but does not explain what it means semantically. 'url_pattern' example '*docs*' suggests wildcard syntax but this is not formally specified.
extract_youtube_transcripts_batch and search_google_batch lack pagination or limit documentation. Batch tools should return success/failure per item and handle partial failures, but no guidance is provided.
Tool descriptions are generic. E.g., 'Crawl a URL and extract content...' does not explain WHEN to use crawl_url vs extract_structured_data. LLMs cannot disambiguate without explicit guidance on intended use cases.