Customer Intelligence & Segmentation
RemoteAbout Customer Intelligence & Segmentation
A remote MCP server for sales teams that tiers customers from purchase history and highlights accounts to retain or grow. For larger files, it provides a script to score data locally.
Key features
- 01A/B/C/D customer tiers
- 02Flags slipping and growing accounts
- 03Estimates revenue risk and upside
- 04Builds SAVE / GROW / VERIFY call lists
- 05Local scoring script for large files
Use cases
- 01Prioritize customers for sales calls
- 02Identify accounts at risk of going quiet
- 03Find customers ready for growth
MCP support
Exposes customer-tiering tools through a remote Streamable HTTP MCP server. OAuth 2.1 sign-in is supported; large files can be scored locally using a returned Python script.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://customer-tiering-mcp-latest.saifs.ai/mcpclaude mcp add --transport http ai-saifs-customer-intelligence https://customer-tiering-mcp-latest.saifs.ai/mcp{"mcpServers":{"ai-saifs-customer-intelligence":{"type":"http","url":"https://customer-tiering-mcp-latest.saifs.ai/mcp"}}}Open in Cursor{"servers":{"ai-saifs-customer-intelligence":{"type":"http","url":"https://customer-tiering-mcp-latest.saifs.ai/mcp"}}}Open in VS Code{"mcpServers":{"ai-saifs-customer-intelligence":{"type":"http","url":"https://customer-tiering-mcp-latest.saifs.ai/mcp"}}}{"mcpServers":{"ai-saifs-customer-intelligence":{"serverUrl":"https://customer-tiering-mcp-latest.saifs.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMECustomer Intelligence & Segmentation
Ranks a customer book into A/B/C/D tiers from purchase history, flags accounts that are slipping or ready to grow, estimates revenue at risk and upside, and builds a short SAVE / GROW / VERIFY call list for sales reps. Works from CSV, Excel, Tally, Salesforce, HubSpot, Zoho or any CRM export with a customer id, a date and an amount.
| Registry name | ai.saifs/customer-intelligence |
| Endpoint | https://customer-tiering-mcp-latest.saifs.ai/mcp |
| Transport | Streamable HTTP (remote, nothing to install) |
| Auth | OAuth 2.1 — PKCE (S256) and dynamic client registration; your client opens a sign-in page on first use |
| Publisher | SAIFS AI |
Install
VS Code / GitHub Copilot
Add to .vscode/mcp.json (workspace) or your user mcp.json:
{
"servers": {
"saifs-customer-intelligence": {
"type": "http",
"url": "https://customer-tiering-mcp-latest.saifs.ai/mcp"
}
}
}
Then start the server from the MCP view and sign in when prompted.
Claude (claude.ai, Desktop)
Settings → Connectors → Add custom connector, and paste:
https://customer-tiering-mcp-latest.saifs.ai/mcp
Claude Code
claude mcp add --transport http saifs-customer-intelligence https://customer-tiering-mcp-latest.saifs.ai/mcp
Any other MCP client
Point it at https://customer-tiering-mcp-latest.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
| Tool | What it does |
|---|---|
customer_tiering | Scores a customer book of up to 500 transaction rows into A/B/C/D tiers (BG/NBD survival model, Gamma-Gamma spend model, tier migration, money layer) and returns decision cards and a per-customer ledger. Cleans customer-name variants before scoring. |
customer_tiering_get_engine | For books over 500 rows: returns a runnable Python script that scores the file locally, so customer data never reaches the server. |
Example prompts
- “Here's our sales export. Who are our A accounts, and who should we call this week?”
- “Which customers are going quiet and how much revenue is at risk?”
- “Why is customer ACME-104 a C account?”
Support
- Website: https://saifs.ai
- Issues: https://github.com/Saify-Technologies/saifs-ai-mcps-docs/issues
- Privacy: https://saifs.ai/privacy_policy
Comments
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