Shopify store intelligence: apps, tech stack, CDN, and market data over a 19K-store corpus.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"storesignal": {
"env": {
"STORESIGNAL_API_KEY": "ss_your_key"
},
"args": [
"storesignal-mcp"
],
"command": "uvx"
}
}
}Are you the author?
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A Model Context Protocol server that exposes the StoreSignal API as tools, so any MCP client (Claude Desktop, Cursor, ChatGPT connectors, or an agent framework) can analyze Shopify stores and run market intelligence queries conversationally.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'storesignal-mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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No known CVEs.
Checked storesignal-mcp against OSV.dev.
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mcp-name: io.github.anthesiallc/storesignal
A Model Context Protocol server that exposes the StoreSignal API as tools, so any MCP client (Claude Desktop, Cursor, ChatGPT connectors, or an agent framework) can analyze Shopify stores and run market intelligence queries conversationally.
It's a thin wrapper: each tool maps to one StoreSignal REST endpoint. All the data work happens in the API.
| Tool | What it does |
|---|---|
analyze_store | Full structured profile for a Shopify store URL (apps, CDN, security headers, schema.org, classification, revenue estimate) |
compare_stores | Side-by-side comparison of 2-5 stores (shared apps, exclusive apps, tier) |
find_stores_using_app | Paginated list of every analyzed store running a specific app |
list_apps | All 278 apps in the catalog, optionally filtered by category |
app_adoption | Top apps by adoption % across the corpus, optionally filtered by category |
app_vs_app | Head-to-head: install counts, overlap, co-install rate, bidirectional cross-adoption |
industry_overview | Per-vertical stats: store count, median price, top countries, top apps, tier mix |
store_census | Whole-corpus stats (19,647 stores, 20 industries, app/tier/type breakdowns) |
get_usage | Current billing period usage and plan limit |
Free tier is 250 calls/month, no credit card:
curl -X POST https://storesignal.anthesia.io/api/v1/signup \
-H 'Content-Type: application/json' \
-d '{"email":"you@example.com"}'
The key comes back in the api_key field of the response.
The easiest way is with uv (no manual venv needed):
# stdio transport (default — for Claude Desktop, Cursor, most local clients)
STORESIGNAL_API_KEY=ss_your_key uvx storesignal-mcp
# streamable-HTTP transport (for remote / web clients)
STORESIGNAL_API_KEY=ss_your_key uvx storesignal-mcp --http
Or install with pip into its own environment:
pip install storesignal-mcp
STORESIGNAL_API_KEY=ss_your_key storesignal-mcp
Note: install into a dedicated environment. The
mcpSDK requires a newerstarlettethan the StoreSignal API app pins, so the two will conflict if installed together.
Environment variables:
STORESIGNAL_API_KEY (required) — your StoreSignal API key.STORESIGNAL_BASE_URL (optional) — defaults to https://storesignal.anthesia.io.STORESIGNAL_TIMEOUT (optional) — request timeout in seconds, default 60.Add to claude_desktop_config.json (Settings → Developer → Edit Config):
{
"mcpServers": {
"storesignal": {
"command": "uvx",
"args": ["storesignal-mcp"],
"env": { "STORESIGNAL_API_KEY": "ss_your_key" }
}
}
}
Add the same block to ~/.cursor/mcp.json (or the project .cursor/mcp.json).
The server is hosted on Smithery, so MCP clients that support Smithery can connect without installing anything. You provide your StoreSignal API key in the Smithery config and it routes to the server.
Any LangChain or LangGraph agent can use these tools through
langchain-mcp-adapters:
# pip install langchain-mcp-adapters langgraph "langchain[anthropic]"
from langchain_mcp_adapters.client import MultiServerMCPClient
client = MultiServerMCPClient(
{
"storesignal": {
"transport": "stdio",
"command": "uvx",
"args": ["storesignal-mcp"],
"env": {"STORESIGNAL_API_KEY": "ss_your_key"},
}
}
)
tools = await client.get_tools()
# hand `tools` to a LangGraph/LangChain agent, e.g.
# from langgraph.prebuilt import create_
... [View full README on GitHub](https://github.com/anthesiallc/storesignal-mcp#readme)