Use Enterprise Cross-Sell Engine with your AI.
Connect your account once and let the AI you already use work with it, without building another integration. Analyzes cross-sell efficiency, product affinity, and customer alignment.
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.
Complete set · 4 capabilities
The complete Enterprise Cross-Sell Engine capability set.
These are the exact actions your AI can choose when you ask it to work with Enterprise Cross-Sell Engine.
01-04
4 capabilities in this set.
Part of 4 available through Enterprise Cross-Sell Engine.
- 01
Calculate success metrics
Calculates the current cross-sell efficiency metrics
- 02
Analyze product affinity
Analyzes the strength of relationships between product pairs
- 03
Generate cross sell playbook
Generates actionable strategic recommendations for sales teams
- 04
Evaluate customer fit
Evaluates how well a product matches a customer's needs
One connector, every AI
Enterprise Cross-Sell Engine 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.
Claude
ChatGPT
Gemini
Perplexity
Grok
Microsoft Copilot
Cursor
VS Code
Windsurf
JetBrains
Cline
LangChain
Vercel AI SDK
Lovable
Z.ai
Raycast
Qwen Code
Kimi Code
Le ChatBuilding your own app? The connector is yours to use.
You don't need a client to put Enterprise Cross-Sell Engine 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
885ms average. Fast in production.
Enterprise Cross-Sell Engine is checked daily against the live service.
- Fastest day
- 710ms
- Slowest day
- 1058ms
- 14-day trend
- Improving-12%
Connect your client
One URL. Every client.
Activate the Connector, copy your link, and paste it into the client you already use. 4 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 Enterprise Cross-Sell Engine, so you can see the experience inside your AI.
It does not authenticate your account with Enterprise Cross-Sell Engine. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.
Enterprise Cross-Sell Engine Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_z2vgT2hB5hUpCXFgIQ4gUUMpjT4NYHADlgj6m7WR/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Enterprise Cross-Sell Engine capabilities are ready to use.
{
"mcpServers": {
"enterprise-cross-sell-success-rate-engine-mcp": {
"url": "https://edge.vinkius.com/vk_preview_z2vgT2hB5hUpCXFgIQ4gUUMpjT4NYHADlgj6m7WR/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? link.label
FAQ
Questions Enterprise Cross-Sell Engine owners ask.
- 01
How do I calculate my current cross-sell efficiency?
You can use the calculate_success_metrics capability by providing the total number of opportunities and the number of closed sales.
- 02
Can this capability help identify which products to bundle?
Yes, the analyze_product_affinity capability identifies product combinations with high historical correlation to suggest effective bundles.
- 03
How does the engine provide sales recommendations?
The generate_cross_sell_playbook capability synthesizes success rates, affinity data, and fit scores into a prioritized list of tactical instructions.
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