Connects Claude to the Jungle Scout Developer API for Amazon product research and keyword intelligence. Exposes five tools: keyword search volume with PPC bid estimates, ASIN keyword rankings, product database queries filtered by category and revenue, sales estimates, and brand share of voice analysis. Requires a Jungle Scout subscription with API access. Useful when you're doing competitive analysis on Amazon listings, hunting for product opportunities by filtering on revenue and review count, or building keyword strategies around search volume and ranking difficulty. Part of a broader product research suite that includes Keepa and Google Trends integrations.
JUNGLESCOUT_API_KEY*secretJungle Scout API key from the Developer/Cobalt API settings
JUNGLESCOUT_KEY_NAME*Jungle Scout API key name (used in the Authorization header as KEY_NAME:API_KEY)
MCP server for the Jungle Scout Cobalt/Developer API: keyword search volume, ASIN keyword analysis, product database queries, sales estimates, and share of voice.
Unofficial: This project is not affiliated with, endorsed by, or sponsored by Jungle Scout. "Jungle Scout" is a trademark of Jungle Scout Group LLC. All rights belong to their respective owners.
| Tool | Description | Example prompt |
|---|---|---|
keyword_search_volume | Exact-match and broad-match volume for up to 100 keywords, plus 30-day trend, quarterly trend, and PPC bid estimates | "What is the search volume for 'yoga mat' and 'foam roller' on Amazon?" |
keywords_by_asin | Which keywords drive traffic to a specific Amazon listing | "What keywords is ASIN B07XJ8C8F5 ranking for?" |
product_database_query | Find product opportunities filtered by category, title keywords, price, minimum revenue, and max reviews | "Find Sports and Outdoors products under $40 with at least $5k monthly revenue and fewer than 300 reviews" |
sales_estimates | Estimated monthly units sold and revenue for an ASIN | "How many units per month does B07XJ8C8F5 sell?" |
share_of_voice | Brand share of organic and sponsored results for a keyword | "Which brands dominate the 'protein powder' keyword on Amazon?" |
Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or
%APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"junglescout": {
"command": "npx",
"args": ["-y", "junglescout-mcp"],
"env": {
"JUNGLESCOUT_API_KEY": "your-api-key-here",
"JUNGLESCOUT_KEY_NAME": "your-key-name-here"
}
}
}
}
Restart Claude Desktop after saving.
claude mcp add junglescout \
-e JUNGLESCOUT_API_KEY=your-api-key-here \
-e JUNGLESCOUT_KEY_NAME=your-key-name-here \
-- npx -y junglescout-mcp
Add to ~/.codex/config.toml:
[mcp_servers.junglescout]
command = "npx"
args = ["-y", "junglescout-mcp"]
[mcp_servers.junglescout.env]
JUNGLESCOUT_API_KEY = "your-api-key-here"
JUNGLESCOUT_KEY_NAME = "your-key-name-here"
The Jungle Scout Developer API requires an active Jungle Scout subscription that includes API access.
Sign up or upgrade your Jungle Scout plan: https://www.junglescout.com/pricing/
Once you have a plan with API access:
export JUNGLESCOUT_API_KEY="your-api-key-here"
export JUNGLESCOUT_KEY_NAME="your-key-name-here"
The server will start without credentials and tools will return setup instructions until both variables are configured.
Keyword research for a new product:
"Give me the Amazon US search volume and PPC bid estimates for 'bamboo cutting board', 'wooden cutting board', and 'plastic cutting board'. Which has the best volume-to-competition ratio?"
The model calls keyword_search_volume with all three terms, compares volumes and ease-of-ranking scores, and summarizes which keyword is the best entry point.
Competitor keyword gap analysis:
"I am competing with ASIN B07XJ8C8F5. What are the top 20 keywords driving traffic to that listing?"
The model calls keywords_by_asin and returns the ranking keywords sorted by relevancy, including organic and sponsored positions.
Product opportunity discovery:
"Find me product opportunities in the Kitchen category priced between $20 and $60 with at least $8,000 monthly revenue and fewer than 150 reviews."
The model calls product_database_query with the filters and returns a ranked list of products with revenue, BSR, and listing quality scores.
# Install dependencies
npm install
# Run tests (no live API calls)
npm test
# Build
npm run build
# Run locally (credentials required for live data)
JUNGLESCOUT_API_KEY=xxx JUNGLESCOUT_KEY_NAME=yyy node dist/index.js
The Jungle Scout API uses a custom authorization format:
Authorization: <KEY_NAME>:<API_KEY>
X-API-Type: junglescout
Content-Type: application/vnd.api+json
Accept: application/vnd.junglescout.v1+json
The Accept header selects the API version and must be the
application/vnd.junglescout.v1+json media type. Sending a different
Accept value causes the API to return HTTP 404.
All marketplace parameters default to us. Other supported values include ca, uk, de, fr, it, es, jp, au, in, and more.
Built by Puya Ventures LLC. I build custom MCP servers and AI integrations for product, e-commerce, and data teams. Get in touch: purahmanian@gmail.com | Portfolio: puyarahmanian.com
Part of the Product-Research MCP Suite: keepa-mcp · google-trends-mcp · junglescout-mcp
This server runs entirely on your machine. It collects no telemetry and stores no data. The only network calls it makes are to the Jungle Scout API (developer.junglescout.com), sending your API credentials and the keywords or ASINs you ask about. Credentials are read from the JUNGLESCOUT_API_KEY and JUNGLESCOUT_KEY_NAME environment variables and never written to disk or sent anywhere except Jungle Scout. See Jungle Scout's privacy policy: https://www.junglescout.com/privacy/
MIT. See LICENSE.
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