KiezelPay Sales MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@KiezelPay Sales MCPWhat's my sales summary for today?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
KiezelPay Sales MCP
An MCP client + server that lets you talk to your KiezelPay merchant sales data in natural language. Claude picks which reporting call to make, your products become attachable context, and common analyses are one-word commands.
The read-only KiezelPay merchant reporting API is wrapped as:
Tools (Claude calls these autonomously)
get_sales_summary- balance, totals, active trials, next/previous payoutget_sales_today/get_sales_yesterday- your sales vs. the best merchant + your rank (optionalplatform)get_purchase_history- recent individual purchases (limit,platform,sort)list_products- distinct product names, derived from historyget_product_sales- aggregated stats for one product
Resources - your products (derived by aggregating the
productfield across purchase history)kpay://products- list of product nameskpay://products/{product}- one product's aggregate (count, revenue*, countries, platforms, first/last sale)
Prompts - one-word analyses
/analyze-product <product>- performance deep-dive/trend-product <product>- trajectory over the available history window/predict-product <product>- near-term estimate (a heuristic extrapolation, not a statistical forecast)/sales-report- overall executive summary
* revenue is included only if the history records carry a price field.
Prerequisites
Python 3.10+
An Anthropic API key (for the chat host)
A KiezelPay merchant API key - get it at https://kiezelpay.com/account/api
The public test key
0123456789abcdef0123456789abcdefworks for summary/today/yesterday, but not/history, so products and the product prompts need a real key.
Setup
1. Configure environment variables
Copy .env.example to .env and fill in the values:
ANTHROPIC_API_KEY="" # your Anthropic API key
CLAUDE_MODEL="claude-sonnet-5"
KIEZELPAY_API_KEY="" # your KiezelPay merchant key
USE_UV="1"The KiezelPay key is used only by the MCP server, is read from the environment, and is
never returned to the model or printed. .env is gitignored.
2. Install dependencies
Using uv (recommended):
uv venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
uv pip install -e .Or without uv:
python -m venv .venv
source .venv/bin/activate
pip install anthropic python-dotenv prompt-toolkit "mcp[cli]>=1.8.0" "httpx>=0.27.0"3. Run the chat host
uv run main.py # or: python main.pyUsage
Chat naturally - Claude will call the right tools:
> How did sales go today, and what's my current balance?
> Which products sold the most in the last 200 purchases?Attach a product as context with @ (Tab to autocomplete):
> How is @RadPro doing lately?Run an analysis prompt with / (Tab to autocomplete):
> /analyze-product RadPro
> /trend-product RadPro
> /predict-product RadPro
> /sales-reportUse from Claude Desktop / Claude Code
The server speaks stdio, so any MCP host can run it. Example Claude Desktop entry:
{
"mcpServers": {
"kiezelpay": {
"command": "uv",
"args": ["run", "mcp_server.py"],
"cwd": "/absolute/path/to/kiezelpay-mcp",
"env": { "KIEZELPAY_API_KEY": "your_key_here" }
}
}
}Project layout
File | Role |
| KiezelPay Sales MCP server (tools, product resources, prompts) |
| Thin async HTTP client for the KiezelPay merchant API + product aggregation |
| Generic MCP client + a small test harness ( |
| CLI chat host entry point |
| Chat host internals (Claude wrapper, chat loop, tool manager, CLI I/O) |
Notes & caveats
The API is read-only; this MCP never mutates anything.
Products are derived from history, so the catalog only reflects the fetched window (
CATALOG_LIMITinmcp_server.py, default 200). Raise it for a longer catalog./predict-productis a reasoning-based estimate over past patterns, not a real forecast.If
today/yesterdayday boundaries look off, adjust the timezoneoffsetinkpay_api.py(tz_offset_minutes()).
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