Model Context Protocol (MCP) server that integrates AgentQL data extraction capabilities.
Single tool with basic schema and description. Tool name 'extract-web-data' uses verb-noun pattern (good), but description lacks critical context about prerequisites, rate limits, or failure modes. Input schema is present with proper types and descriptions for both parameters (url, prompt). However, no output schema is documented, LLMs cannot predict the structure of returned data. No error handling guidance provided. Tool is read-only (safe), but lacks idempotent/destructive annotations. Baseline: 194 chars avg description; this one is 155 chars (acceptable). Both parameters have descriptions (good). Missing: output schema documentation, error recovery guidance, rate limit warnings.
Extracts structured data as JSON from a web page given a URL using a Natural Language description of the data.
No output schema documented. LLMs cannot predict the structure of json.data returned by AgentQL API. This forces agents to guess field names and types, increasing hallucination risk.
Description lacks prerequisites and failure modes. Does not state: API key requirement, rate limits, supported URL types, or what happens when extraction fails. LLMs cannot plan robustly without this context.
No error handling guidance. Tool throws generic 'AgentQL API error' without recovery hints. If extraction fails, LLM has no guidance on retry strategy, fallback, or user notification.
Missing tool annotations. Tool is read-only and idempotent, but lacks readOnlyHint and idempotentHint annotations. Agents cannot infer safety properties without explicit hints.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 59 | 2026-07-28+ | v2 |
No pagination or result limits documented. If AgentQL returns large datasets, no guidance on truncation, chunking, or pagination. Unbounded results risk context window exhaustion.