Acmezone Data MCP
Provides read-only access to Amazon business data including sales history, current sales, inventory levels, inventory value, and financial records for internal analysis.
Click on "Deploy 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., "@Acmezone Data MCPlist top selling products this month"
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.
Acmezone Data MCP
Acmezone Data MCP is a read-only MCP service for internal company Amazon business data. It encapsulates sales volume, inventory, inventory value, and financial data into 19 Tools, available for WorkBuddy, MCP Inspector, and other MCP-compatible clients.
The two-phase modular refactoring has been completed: both the Tool interface layer and the Repository data access layer are in place, with full regression testing before and after the refactoring. For implementation records, refer to the Refactoring Plan.
Current Status
Python 3.12
MCP Streamable HTTP
Container listening:
0.0.0.0:8000No environment variable configuration; data paths, worksheet names, and ports are currently hardcoded in
settings.py19 Tools have been split into 8 modules by business domain, with existing interfaces remaining compatible
Direct reading of Excel and SQLite has been centralized in the Repository layer
All 19 Tools publish structured output schemas, parameter enums/ranges, and read-only markers
Excel Snapshots are cached by file size and nanosecond-level modification time, automatically invalidated when the source file changes
Excel is opened with
read_only=Trueanddata_only=TrueSQLite financial database is connected in read-only mode via
mode=ro
Current directory:
mcp/
├─ mcp_server.py
├─ settings.py
├─ core/
├─ tools/
├─ repositories/ # Excel、销售、库存和财务数据访问
├─ tests/
├─ scripts/
├─ docs/
├─ requirements.txt
└─ DockerfileRelated MCP server: flin-shopify-analytics-mcp
Data Sources
Business Data | Container Path | Worksheet/Data Table | Container Permission |
Historical Sales and Forecast |
|
| Read-only |
Current Sales |
|
| Read-only |
Current Inventory |
|
| Read-only |
Inventory Quantity and Value |
|
| Read-only |
Historical Finance |
| SQLite | Read-only |
Source file modification time is only used to determine data freshness, no longer to distinguish actual from forecast. The actual/forecast boundary uniformly uses the current month in the company timezone Asia/Shanghai. Financial data additionally uses the report month and upload time in the database to indicate the data cutoff.
Docker Deployment
The current NAS container uses the following storage mounts:
NAS Directory or File | Container Location | Permission | Purpose |
|
| Read/Write | MCP Source Code |
|
| Read-only | Financial Database |
|
| Read-only | Excel Data Files |
Container execution:
python /app/mcp_server.pyThe current Dockerfile only installs dependencies, not copying the source code, because at runtime the entire MCP project directory is mounted to /app. Therefore, if this image runs independently without the /app mount, it will not find mcp_server.py; this is a known prerequisite of the current deployment method.
The service inside the container listens on port 8000. The NAS external port is determined by the "port mapping" configuration in the container management interface.
Tool Overview
Products
search_productget_product_catalog_summaryget_parent_childrenget_product_overviewcompare_product_overviews
Sales
get_sales_historyget_current_salesget_sales_rankingget_sales_trend_ranking
Inventory
get_inventoryget_inventory_valueget_inventory_ranking
Finance, Forecast, and System
get_finance_historyget_finance_rankingget_replenishment_forecastget_product_batchfilter_productsget_data_source_statusget_data_quality_report
For parameters and usage of each Tool, refer to the Tool Interface Reference.
Install Dependencies
pip install -r requirements.txtCurrent dependencies:
mcp[cli]==2.0.0openpyxl==3.1.5pydantic==2.13.4
Core runtime dependencies are version-locked. Before upgrading dependencies or rebuilding the image, a full regression test should still be run.
Startup
Execute within a container that has /storage and /finance data mounts:
python /app/mcp_server.pyRunning locally can start the service, but if the corresponding absolute data paths do not exist, data query Tools will return that the data file does not exist or is inaccessible.
Maintenance Principles
Do not modify the original Excel or financial database.
Tools only read and organize real business data; they do not replace AI for business judgment.
When modifying a Tool, maintain backward compatibility of names, parameters, and return structures.
During refactoring, after migrating each module, recheck the Tool registration count and representative responses.
When modifying a Tool, the interface reference, architecture documentation, and employee usage documentation must be updated simultaneously.
Documentation consistency check:
python scripts/check_documentation_consistency.pyProject Documentation
This server cannot be deployed
Maintenance
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