F
licenseNot graded
qualityB
maintenanceEnables aspect-level sentiment mining from customer reviews and produces satisfaction radar breakdowns with structured output for AI agents.
8
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WizerAPI Review Intelligence
by com.wizerapi
Server Details
Analyze customer reviews: sentiment, emotion, topics, themes, digests, and drafted replies.
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- Status
- Unhealthy
- Uptime
- 3.4% over 66 days
- Last Tested
- Transport
- Streamable HTTP
- URL
TDQS
A4.4/5.0
Scored across 5 tools
Disambiguation4/5
The single-review vs. review-set split (analyze_review/draft_reply vs. extract_themes/summarize_reviews) is clearly delineated by input scope and descriptions. However, draft_reply overlaps with analyze_review's options.suggest_reply, and extract_themes vs. summarize_reviews both operate on sets, requiring the descriptions' guidance to disambiguate. Descriptions handle these overlaps well but they still exist.
Naming Consistency5/5
All five tools follow a strict verb_noun snake_case pattern: analyze_review, check_usage, draft_reply, extract_themes, summarize_reviews. The verb choices are consistent and predictable, and the noun clearly identifies the target resource or operation.
Tool Count5/5
Five tools is well-scoped for a review-intelligence API, with each tool covering a distinct capability: single analysis, reply drafting, theme clustering, set summarization, and quota checking. Nothing feels redundant or missing from a count perspective.
Completeness4/5
The surface covers the full review workflow: analyze individual reviews, aggregate themes, produce executive digests, draft replies, and monitor quota. Minor gaps exist (e.g., no batch or async job status tool for very large metered sets), but agents can reasonably work around these.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
5 tool updates
- First observed
analyze_review - First observed
check_usage - First observed
draft_reply - First observed
extract_themes - First observed
summarize_reviews
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