# Inventory Turnover MCP > Inventory Turnover Calculator provides immediate visibility into how fast you sell through stock and keep cash flowing. It calculates key metrics like turnover ratio and Days Sales of Inventory (DSI), then compares your performance directly against established industry benchmarks for Retail, Manufacturing, and Distribution sectors. ## Overview - **Category:** finance - **Price:** Free - **Tags:** inventory, turnover, cogs, retail, logistics ## Description This MCP helps finance teams stop guessing about their inventory health. Instead of running complex manual calculations in Excel, you feed it basic data—like your annual Cost of Goods Sold and average stock value—and it immediately spits out crucial efficiency metrics. You get the Turnover Ratio, DSI, and daily inventory spend, all calculated instantly. But that's only half the story. The real value is comparison. It pulls in industry best practices to show you whether your current performance is optimal or if there's a serious bottleneck somewhere down the line. If you're building out a central data hub, connecting this through Vinkius gives you immediate access to these crucial financial standards right where your agent works. ## Tools ### analyze_sector_efficiency Compares your current inventory metrics against industry standards to identify operational weak spots. ### calculate_turnover_metrics Runs the necessary numbers to generate your core turnover ratio, DSI, and daily inventory value figures. ### get_industry_benchmarks Retrieves target benchmark ranges for different industries like Retail, Manufacturing, and Distribution. ## Prompt Examples **Prompt:** ``` Calculate my inventory metrics with an annual COGS of 500000 and average inventory value of 50000. ``` **Response:** ``` Your Inventory Turnover Ratio is 10.0, your Days Sales of Inventory (DSI) is 36.5 days, and your daily inventory value is approximately $136.99. ``` **Prompt:** ``` What are the industry benchmarks for turnover? ``` **Response:** ``` The target ranges are: Retail (6-12x), Manufacturing (4-8x), and Distribution (8-15x). ``` **Prompt:** ``` Is a turnover ratio of 5.0 good for the Manufacturing sector? ``` **Response:** ``` A turnover ratio of 5.0 is considered Optimal for the Manufacturing sector, as it falls within the target range of 4 to 8 times per year. ``` ## Capabilities ### Calculate core inventory metrics Determine your current turnover ratio, Days Sales of Inventory (DSI), and daily inventory value using basic COGS and average stock figures. ### Compare against industry standards Retrieve target performance ranges for major sectors like Retail, Manufacturing, and Distribution to benchmark your own numbers. ### Assess operational efficiency gaps Evaluate how far off-the-mark your current metrics are compared to established industry best practices. ## Use Cases ### Determining if the new warehouse layout improved flow A Supply Chain Manager needs to know if their recent operational changes helped. They ask the agent to run `calculate_turnover_metrics` on Q3 data, then use `analyze_sector_efficiency` to see if the results show a significant jump toward best-in-class Manufacturing benchmarks. ### Preparing for an investor review A Financial Analyst needs quick metrics before a call. They first run `get_industry_benchmarks` to get the latest Retail targets, then use `calculate_turnover_metrics` with their current data to prove they are meeting or beating those standards. ### Investigating slow sales periods The Operations Director suspects a specific product line is hoarding cash. They run the metrics, and when `analyze_sector_efficiency` flags a poor DSI compared to Distribution norms, they know exactly where to focus their attention. ## Benefits - Get immediate calculation of key metrics. Use `calculate_turnover_metrics` to get the Turnover Ratio, DSI, and daily inventory spend in one go. - Stop comparing apples to oranges. The MCP uses `get_industry_benchmarks` to provide clear target ranges for your sector, so you know what 'good' actually looks like. - Pinpoint exact bottlenecks. Run `analyze_sector_efficiency` to see which operational area is dragging down performance compared to the industry average. - Faster decision-making means more cash. Quick access to these metrics lets you adjust purchasing or sales strategies immediately, instead of waiting for a weekly report. - Better budget forecasting. Understanding your DSI helps finance teams accurately predict how much working capital is tied up in slow-moving stock. ## How It Works The bottom line is you get an instant, comparative audit of your stockroom efficiency without opening a single spreadsheet. 1. You input the necessary financial data, specifically annual COGS and average inventory value. 2. The MCP runs those numbers through its calculation tool and pulls in relevant industry benchmarks for your sector. 3. It generates a clear report showing your metrics alongside the optimal target range, highlighting where you fall short or exceed expectations. ## Frequently Asked Questions **How do I use `calculate_turnover_metrics`?** You need to provide two numbers: your annual Cost of Goods Sold (COGS) and your average inventory value. The tool then generates the core ratios for you. **What sectors does `get_industry_benchmarks` cover?** It provides benchmark ranges for major commercial categories, including Retail, Manufacturing, and Distribution. You just need to specify your industry type. **Does this MCP help with predictive inventory models?** No, it doesn't predict the future. It tells you how efficient you *are* right now by comparing current metrics against established best-practice ranges. **Is there a difference between `analyze_sector_efficiency` and just calculating turnover?** Yes, running `analyze_sector_efficiency` goes beyond math. It takes the calculated metrics and actively compares them against industry goals to point out specific problems. **What data parameters does `calculate_turnover_metrics` require for accurate results?** You need three core financial inputs: annual Cost of Goods Sold (COGS), average inventory value, and the time frame. The tool uses COGS and average inventory to determine your turnover ratio and Days Sales of Inventory (DSI). Always ensure these figures are from matching fiscal periods for accurate comparison. **How does `analyze_sector_efficiency` handle inconsistent data inputs?** The MCP checks the provided metrics against established sector standards. If your input deviates significantly from expected norms, it highlights that variance and tells you where your performance falls relative to the industry mean. It flags areas needing review. **If I run into an issue with `get_industry_benchmarks`, what might be causing it?** Typically, errors occur when a requested sector code doesn't match our database or if the system needs more context. Try specifying the full industry name instead of using abbreviations. If problems persist, check your client's connection status. **Can `calculate_turnover_metrics` handle data from multiple sources simultaneously?** No, this MCP accepts one clean set of inputs per request. You must gather the annual COGS and average inventory value into a single source first. The tool processes that singular dataset to provide all three key metrics: ratio, DSI, and daily value.