Demand Forecasting
ai.saifsPublished by saifs.aiOfficial publisherv1.0.1Updated Nov 4, 2026
Forecast product demand using historical sales and market signals.
The publisher's own server: Customer Intelligence & Segmentation
Overview
Remote MCP server that forecasts product demand from sales history, returning prediction intervals, the chosen model and lead-time demand.
- What you can do
- Forecast demand per product, optionally by region or channel, from daily, weekly or monthly sales rows, with a prediction interval for every number
- Get the selected model, its backtest score and lead-time demand for reordering
- Handle slow and intermittent movers and refuse to guess when history is too short
- Read Excel, Tally and CSV exports with their own column names
- Generate a runnable Python script that reproduces the same forecasts locally for larger files
- When to use it
- Useful when you have sales history and want forward demand estimates for planning, reordering or reviewing slow movers, without building a forecasting pipeline yourself. Suited to small to medium datasets (about 200 products and 2,500 rows) or to generating a local script for bigger ones.
- Requirements
- A remote Streamable HTTP endpoint; nothing to install. OAuth 2.1 sign-in with PKCE and dynamic client registration, so the client opens a sign-in page on first use. Sales data is supplied as rows or file exports.
Installation
In SourceWeft
- Open Demand Forecasting in the dashboard and add it to a workspace.
- Connect the required credentials. They are stored privately and never shown on public pages.
- Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Use with an agent
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/ai.saifs%2Fdemand-forecasting/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Other MCP clients
Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.
{
"mcpServers": {
"demand-forecasting": {
"type": "http",
"url": "https://demand-forecaster-mcp.saifs.ai/mcp"
}
}
}README
Demand Forecasting
Forecasts demand per product (and optionally per region or channel) from sales history — daily, weekly or monthly — with a range for every number. It picks the best-fitting model by backtest, handles slow and intermittent movers (Croston/SBA), refuses to guess when history is too short, and hands lead-time demand to the Inventory Intelligence & Optimizer server for safety stock. Reads Excel, Tally and CSV exports with their own column names.
Install
VS Code / GitHub Copilot
Add to .vscode/mcp.json (workspace) or your user mcp.json:
Then start the server from the MCP view and sign in when prompted.
Claude (claude.ai, Desktop)
Settings → Connectors → Add custom connector, and paste:
Claude Code
Any other MCP client
Point it at https://demand-forecaster-mcp.saifs.ai/mcp using the Streamable HTTP transport. The server returns 401 with a
WWW-Authenticate: Bearer … resource_metadata=… challenge, so OAuth-aware clients sign in automatically.
Tools
Example prompts
- “Here's our Tally sales export. How much of each item will we sell over the next 13 weeks?”
- “Which products are slow movers, and what should we expect from them next month?”
- “Forecast monthly demand for spare part SP-220 with a 95% range.”
Support
- Website: https://saifs.ai
- Issues: https://github.com/Saify-Technologies/saifs-ai-mcps-docs/issues
- Privacy: https://saifs.ai/privacy_policy
Source: servers/demand-forecasting/README.md at commit 2b4eab8
Tools
0Version history
2- v1.0.1LatestOct 21, 2026
- v1.0.0Sep 16, 2026
Score
85% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 daysRequired25 pts
- Auth declaredRequired10 pts
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
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