Server data from the Official MCP Registry
Amazon data MCP: products, rankings, reviews, niches, WIPO & PACER IP, AI search & trends.
Amazon data MCP: products, rankings, reviews, niches, WIPO & PACER IP, AI search & trends.
Remote endpoints: streamable-http: https://mcp.pangolinfo.com/mcp?api_key={api_key}
Pangolinfo MCP is a well-structured, read-only data aggregation server with proper authentication, clear permission scoping, and good code quality. It requires an API key for all backend operations, implements secure HTTP-only transport, and provides both stdio and HTTP modes with appropriate per-request isolation. Minor findings relate to broad exception handling and the inherent trust model of passing user API keys, which are expected for this class of service. Supply chain analysis found 3 known vulnerabilities in dependencies (0 critical, 2 high severity).
5 files analyzed · 8 issues found
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Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
Pangolinfo MCP server — 18 Amazon e-commerce & IP data tools for AI assistants via Model Context Protocol.
Plug your favorite AI client (Claude Code, Cursor, Cline, Windsurf, Codex, Hermes, OpenClaw) into Pangolinfo's Amazon scrape APIs and let the AI run keyword research, listing analysis, review mining, niche discovery, category navigation, AI search lookups, keyword-trend checks, and WIPO trademark clearance — all from natural-language instructions.
⚠️ BREAKING CHANGE in 0.3.0 — tool renames (no backward-compatible aliases)
Old name (≤ 0.2.x) New name (0.3.0+) google_ai_searchai_searchgoogle_trendskeyword_trendsTool names changed to remove third-party brand references from the public MCP interface. Any prompts, SKILLs, or scripts pinning the old names will get
ToolNotFoundafter upgrading. Update your prompts to the new names. Tool parameters, return shape, and pricing are unchanged.
| Version | 0.5.0 |
| Tools | 18 (17 backend + 1 self-introspection) |
| Transport | stdio (MCP standard) |
| Runtime | Node.js 18+ |
| License | MIT |
| Get an API key | https://tool.pangolinfo.com/ |
The Pangolinfo Installer detects your AI client, writes the right config files, and you're done. Pass --scope=mcp to install only this MCP server (skip the Skills package).
macOS / Linux
curl -fsSL https://pangolinfo.dev/install.sh | sh -s -- \
--agent=<your-agent> \
--scope=mcp \
--api-key=pgl_xxxxxxxxxxxx
Windows (PowerShell)
irm https://pangolinfo.dev/install.ps1 | iex; `
Install-Pangolinfo -Agent <your-agent> -Scope mcp -ApiKey pgl_xxxxxxxxxxxx
<your-agent> is one of: claude-code, cursor, cline, windsurf, codex, hermes, openclaw.
After the installer finishes, restart your AI client so it picks up the new mcpServers entry.
The release artifact is a single self-contained server.mjs (~800 KB) — all dependencies are bundled in. No npm install needed.
# macOS / Linux
mkdir -p ~/.local/lib/pangolinfo-mcp
curl -fsSL https://github.com/pangolinfo/pangolinfo-mcp/releases/latest/download/server.mjs \
-o ~/.local/lib/pangolinfo-mcp/server.mjs
chmod +x ~/.local/lib/pangolinfo-mcp/server.mjs
# Windows (PowerShell)
$dir = "$env:LOCALAPPDATA\pangolinfo-mcp"
New-Item -ItemType Directory -Force -Path $dir | Out-Null
irm https://github.com/pangolinfo/pangolinfo-mcp/releases/latest/download/server.mjs `
-OutFile "$dir\server.mjs"
Then wire it into your AI client — see the per-client snippets below. Point args at the file you just downloaded.
Developers: to build from source,
git clonethis repo and runnpm install && npm run build. The produceddist/server.mjsis identical to the release asset.
pgl_xxxxxxxx key from the dashboardpangolinfo_capabilities is free)Replace /abs/path/to/pangolinfo-mcp/dist/server.mjs with your real path, and pgl_xxxxxxxx with your key.
~/.claude/settings.json){
"mcpServers": {
"pangolinfo": {
"command": "node",
"args": ["/abs/path/to/pangolinfo-mcp/dist/server.mjs"],
"env": { "PANGOLINFO_API_KEY": "pgl_xxxxxxxx" }
}
}
}
Prefer
claude mcp add --scope user pangolinfo node /abs/path/to/dist/server.mjs— it writes the same entry without hand-editing JSON.
~/.cursor/mcp.json){
"mcpServers": {
"pangolinfo": {
"command": "node",
"args": ["/abs/path/to/pangolinfo-mcp/dist/server.mjs"],
"env": { "PANGOLINFO_API_KEY": "pgl_xxxxxxxx" }
}
}
}
Open Cline → MCP Servers → Edit settings JSON, then add:
{
"mcpServers": {
"pangolinfo": {
"command": "node",
"args": ["/abs/path/to/pangolinfo-mcp/dist/server.mjs"],
"env": { "PANGOLINFO_API_KEY": "pgl_xxxxxxxx" }
}
}
}
The settings file lives at <vscode-user>/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json.
If you're on the standalone Cline CLI, use ~/.cline/data/settings/cline_mcp_settings.json instead.
~/.codeium/windsurf/mcp_config.json){
"mcpServers": {
"pangolinfo": {
"command": "node",
"args": ["/abs/path/to/pangolinfo-mcp/dist/server.mjs"],
"env": { "PANGOLINFO_API_KEY": "pgl_xxxxxxxx" }
}
}
}
~/.codex/config.toml)[mcp_servers.pangolinfo]
command = "node"
args = ["/abs/path/to/pangolinfo-mcp/dist/server.mjs"]
[mcp_servers.pangolinfo.env]
PANGOLINFO_API_KEY = "pgl_xxxxxxxx"
~/.hermes/config.yaml)mcp_servers:
pangolinfo:
command: node
args: ["/abs/path/to/pangolinfo-mcp/dist/server.mjs"]
env:
PANGOLINFO_API_KEY: pgl_xxxxxxxx
~/.openclaw/openclaw.json){
"mcpServers": {
"pangolinfo": {
"command": "node",
"args": ["/abs/path/to/pangolinfo-mcp/dist/server.mjs"],
"env": { "PANGOLINFO_API_KEY": "pgl_xxxxxxxx" }
}
}
}
See MCP-TOOLS-MAP.md for the full coordination graph (which tools chain into which).
| # | Tool | Purpose | Cost (credits) |
|---|---|---|---|
| 1 | search_amazon | Amazon keyword search → structured product list | 0.75 |
| 2 | get_amazon_product | Single-ASIN listing detail (title / bullets / features / aiReviewsSummary) | 0.75 |
| 3 | get_amazon_reviews | Batch reviews for an ASIN (VOC mining) | 0.75 |
| 4 | list_bestsellers | Amazon Bestsellers by category | 0.75 |
| 5 | list_new_releases | Amazon New Releases by category | 0.75 |
| 6 | list_seller_products | Catalog of products under one seller | 0.75 |
| 7 | list_category_products | All products in a category leaf | 0.75 |
| 8 | search_categories | Search Amazon category tree by keyword | 0.75 |
| 9 | get_category_children | Drill down one level in the category tree | 0.75 |
| 10 | filter_categories | Filter category nodes by criteria | 0.75 |
| 11 | filter_niches | Niche discovery (size × competition × growth) | 0.75 |
| 12 | get_category_paths | Resolve full ancestor paths for a category node | 0.75 |
| 13 | search_local_maps | Google Maps local business search | 0.75 |
| 14 | wipo_search | WIPO global design / trademark search (IP clearance) | 2 |
| 15 | pacer_search | US patent-litigation (PACER) case + docket timeline search | 12 |
| 16 | ai_search | AI Search via Google SERP (AI Overview + organic, with compliance disclaimer) | 2 |
| 17 | keyword_trends | Keyword Trends via Google Trends (with compliance disclaimer) | 1.5 |
| 18 | pangolinfo_capabilities | Self-introspection — what tools exist, how they chain | 0 (local) |
Default marketplace is Amazon US (marketplaceId=ATVPDKIKX0DER, zip=90001). Override per call via tool arguments.
The server resolves the API key with this priority:
--api-key=pgl_xxx --api-base=... --scrape-base=...PANGOLINFO_API_KEY, PANGOLINFO_API_BASE, PANGOLINFO_SCRAPE_BASE~/.pangolinfo/config.json:
{
"api_key": "pgl_xxxxxxxxxxxx",
"api_base": "https://extapi.pangolinfo.com",
"scrape_base": "https://scrapeapi.pangolinfo.com"
}
CLI args win over env vars — convenient when you want per-server keys without polluting the global environment.
The server returns Chinese descriptions and error hints by default. Set PANGOLINFO_LANG=en to switch to English:
"env": {
"PANGOLINFO_API_KEY": "pgl_xxxxxxxx",
"PANGOLINFO_LANG": "en"
}
Startup logs are always English (operator-facing); tool descriptions and error hint fields follow PANGOLINFO_LANG.
After restarting your AI client, ask it:
List all available
pangolinfoMCP tools.
You should see 18 tools. Then try:
Use
pangolinfo_capabilitieswith mode "summary".
This is a free local call — if it returns the tool catalog, your install is wired correctly. Next, run something paid like:
Search Amazon for "wireless mouse" and return the top 5 results.
Expected: ~0.75 credits deducted, ~300 KB of structured product data returned.
npm install
npm run dev # tsx src/server.ts — hot-reload
npm run build # esbuild → dist/server.mjs
npm run typecheck # tsc --noEmit
npm start # node dist/server.mjs
src/
├── server.ts MCP stdio entry + tool registration
├── auth.ts API key resolution (CLI > env > config file)
├── client.ts HTTP client (Authorization, User-Agent)
├── errors.ts PangolinfoError + status-code mapping
├── config.ts Default endpoints / constants
├── i18n.ts zh/en translation lookup
└── tools/
├── _types.ts Tool / ToolContext type definitions
├── index.ts Tool registry (18 tools)
└── <verb_noun>.ts One file per tool
src/tools/<verb_noun>.ts exporting a Tool object — mirror search_amazon.ts.src/tools/index.ts and append to the tools array.zod; .describe() every field — the AI reads those.fetch directly — use ctx.client.post(...). Auth is already injected.PangolinfoError on failure; the HTTP client already throws this for non-2xx responses.We take operator and user safety seriously. By design, this MCP server:
PANGOLINFO_API_KEY (issued at https://tool.pangolinfo.com/). The key is read locally from your AI client's config or environment — it is never transmitted anywhere except to https://scrapeapi.pangolinfo.com (or https://mcp.pangolinfo.com for the hosted variant) over TLS 1.2+.https://mcp.pangolinfo.com/mcp) require HTTPS; HTTP requests are refused.Report security issues privately to security@pangolinfo.com — please do not file public GitHub issues for vulnerabilities.
MIT © Pangolinfo
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