MCP Server Integration for AI-Assisted Quote Building

Summary

Publish an official Salesbuildr MCP (Model Context Protocol) server that wraps the existing Public API, enabling AI assistants — such as Claude Desktop, Claude.ai, or custom LLM workflows — to build and manage quotes, search products, and look up clients through natural language.

Problem

The Salesbuildr Public API is well-structured and already covers the core resources needed for AI-assisted quoting: Products, Quotes, Quote Templates, Companies, Contacts, Opportunities, Pricing Books, and Discount Groups. The foundation is there

The gap is that there is no MCP-compliant interface on top of it. MCP is the emerging standard protocol that allows AI assistants to discover and call application functions natively. Without it, connecting an AI tool to Salesbuildr requires custom integration work that most MSPs won't build themselves — meaning the API's potential for AI-driven workflows goes largely untapped.

What Already Exists (and Could Be Wrapped)

The following existing API endpoints map directly to the MCP tools that would power an AI quoting workflow:

The MCP server would be a thin wrapper around these — defining tool schemas, handling authentication, and making the endpoints discoverable to AI runtimes.

Current Limitation Worth Noting

The Quote endpoint currently supports Create and Order but not Update or Delete via API. For a complete AI quoting workflow, the ability to update an existing quote (add/remove line items, adjust quantities) would be highly valuable. This feature request is asking for MCP first, but an update endpoint for Quote would significantly extend what's possible.

Expected Outcome

With an MCP server in place, an AI assistant could handle a workflow like:

"Build a quote for YourLand for a 50-seat Intune + Defender deployment. Use our standard per-seat licensing, apply the MSP discount group, and create it against the existing YourLand opportunity."

The AI would search the product catalogue, match SKUs, apply the correct pricing book and discount group, look up the company and contact records, and create the quote — without the engineer touching the Salesbuildr UI.

Implementation Notes

• Authentication via existing api-key header — no new auth mechanism needed

• Rate limit of 500 requests per 10-minute window is sufficient for typical AI quoting sessions; the MCP server should implement the recommended exponential backoff on 429 responses

• Webhook events (quote.created, quote.ordered, opportunity.status_changed) could be used to push updates back to AI workflow orchestrators, complementing the MCP tools

• The server could be published as an open-source reference implementation, allowing MSPs to self-host or extend it