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Connect Demand Forecast Calculator to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn historical data into accurate 3-month demand projections.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Demand Forecast Calculator.

  1. 01

    Analyze sma

    This capability calculates demand forecasts using the Simple Moving Average method. It's best for smoothing out short-term fluctuations in stable datasets.

  2. 02

    Analyze exponential smoothing

    This capability uses Exponential Smoothing to project future demand. It's designed to handle data where recent observations carry more weight.

  3. 03

    Analyze wma

    This capability performs Weighted Moving Average calculations. You can assign specific weights to different periods to prioritize recent demand trends.

Real work

What teams actually run

01

Inventory Optimization

Use the MAPE results to determine safety stock levels based on model error rates.

02

Production Scheduling

Generate 3-month demand projections to plan manufacturing runs ahead of time.

03

Trend Validation

Compare SMA and WMA results to see if your demand is stable or trending heavily.

04

Seasonal Adjustment

Apply Exponential Smoothing to data that shows recent shifts in consumer behavior.

Automate a task

Put Demand Forecast Calculator to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Demand Forecast Calculator works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Demand Forecast Calculator to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

807ms average. Fast in production.

Demand Forecast Calculator is checked daily against the live service.

Daily averagePeak 1041ms
Oct 3Today
Fastest day
575ms
Slowest day
1041ms
14-day trend
Improving-21%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Demand Forecast Calculator, so you can see the experience inside your AI.

It does not authenticate your account with Demand Forecast Calculator. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Demand Forecast Calculator Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_sv6aatMHqHyqOR4XjXsLusL61ZUZceGD44vNHlLt/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Demand Forecast Calculator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "demand-forecast-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_sv6aatMHqHyqOR4XjXsLusL61ZUZceGD44vNHlLt/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Demand Forecast Calculator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Demand Forecast Calculator owners hand off.

This MCP is built for professionals managing inventory and production schedules who need to move from raw data to actionable forecasts quickly.

  • 01

    Supply Chain Analysts

    They hand off historical shipment data to the AI to generate baseline demand models.

  • 02

    Inventory Managers

    They use the error metrics to decide which forecasting model will best prevent stockouts.

  • 03

    Operations Planners

    They use the 3-month projections to coordinate production capacity with expected demand.

FAQ

Questions Demand Forecast Calculator owners ask.

  • 01

    What forecasting models does this MCP support?

    It supports Simple Moving Average (SMA), Weighted Moving Average (WMA), and Exponential Smoothing.

  • 02

    How do I know if the forecast is accurate?

    The MCP performs error backtesting for every calculation, providing Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) values.

  • 03

    Which AI clients can I use with this MCP?

    You can use it with any MCP-compatible client, including Claude Desktop, Cursor, Windsurf, and VS Code.

  • 04

    Can I use specific weights for my moving average?

    Yes, the analyze_wma capability allows you to provide specific weights for your historical data points.

  • 05

    How long are the projections?

    The capabilities are designed to generate demand projections for a 3-month period.

  • 06

    What forecasting methods are supported?

    The server supports Simple Moving Average (analyze_sma), Weighted Moving Average (analyze_wma), and Exponential Smoothing (analyze_exponential_smoothing).

  • 07

    How is the accuracy of the forecast measured?

    Accuracy is measured using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) through a backtesting process on your historical data.

  • 08

    What inputs are required for the SMA capability?

    The analyze_sma capability requires an array of historical demand values and a window size representing the number of periods to include in the average.

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