junglescout-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| JUNGLESCOUT_API_KEY | Yes | Your Jungle Scout API key | |
| JUNGLESCOUT_KEY_NAME | Yes | Your Jungle Scout key name |
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 | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| keyword_search_volumeA | Look up exact-match and broad-match search volume for one or more Amazon keywords. |
| keywords_by_asinA | Discover which keywords drive traffic to a specific Amazon listing (by ASIN). |
| product_database_queryA | Search the Jungle Scout product database for Amazon product opportunities. |
| sales_estimatesA | Get Jungle Scout estimated monthly sales units and revenue for a specific ASIN. |
| share_of_voiceB | Analyze brand share of voice for a given Amazon search keyword. |
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 aspect of Amazon product research: keyword volume, keyword-to-ASIN mapping, product database search, sales estimates, and share of voice. No overlap in functionality.
All tool names follow a consistent snake_case pattern and clearly indicate their function (e.g., 'keyword_search_volume', 'sales_estimates'). No mixing of conventions.
With 5 tools, the server is well-scoped for Amazon product research. Each tool serves a necessary purpose without redundancy.
The tool set covers the core workflow: keyword research, product discovery, sales data, and brand analysis. Minor gaps like historical trends or competitor tracking exist but are not essential.