Pangolinfo Amazon Reviews MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| PANGOLINFO_API_KEY | Yes | Your Pangolinfo API key. Get one from the Amazon Review API page. |
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 |
|---|---|
| get_amazon_reviewsA | Fetch a paginated page of Amazon reviews for an ASIN. |
| find_complaint_signalsB | Extract complaint-like reviews and recurring VOC signals from an ASIN review page. |
| summarize_review_ratingsA | Return deterministic rating counts, average rating and review volume from an ASIN review page. |
| filter_review_mediaA | Filter reviews that contain image or video/media evidence. |
| compare_review_pagesA | Compare rating and complaint signals for two ASINs using one review page per product. |
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 5 tools
Each tool targets a distinct action on Amazon review data: fetching raw pages, extracting complaints, summarizing ratings, filtering media, and comparing products. There is little risk of selecting the wrong tool for a task.
All tool names follow a clear lowercase verb_noun pattern with descriptive, specific verbs: get, find, summarize, filter, compare. The naming is consistent and predictable across the entire set.
Five tools is well-scoped for an Amazon reviews analysis server. Each tool covers a distinct aspect of the workflow without unnecessary redundancy or bloat.
The tool set covers core review retrieval, analysis, and comparison workflows well. Minor gaps exist around multi-page aggregation or deeper per-review detail, but agents can accomplish the main review-analysis tasks without dead ends.