Last week I made a claim: your AI assistant can't actually read your pipeline. A lot of people agreed. A few pushed back: "Can't you just use the API?" or "What about RAG?" Fair questions. Let me answer them properly. MCP isn't better because it's newer. It's better because it was designed specifically for this problem. Model Context Protocol is an open standard published by Anthropic. It defines how an AI assistant can discover, call, and receive results from structured tools. Your AI assistant is an extremely capable analyst. MCP is the secure, structured desk where all the right files are waiting — organised, pre-processed, and ready to reason over. You ask in plain English. The tool runs the logic. The AI interprets the result. Here's the flow when you ask Claude: "Analyze my pipeline health" No copy-pasting. No screenshots. No engineering middleware. I spent months translating 15 years of revenue consulting methodology into MCP tools. The result is the Artefact MCP Server — an open-source package that turns Claude into a GTM intelligence advisor. It ships with 7 tools, works with sample data out of the box (no API key required), and installs in 3 steps: pip install artefact-mcp claude mcp add artefact-mcp "Analyze my pipeline health" "Who are my ideal customers?" "What is my dominant growth constraint?" HubSpot shipped their own official MCP server. It's excellent for CRM read/write access. Artefact MCP brings analytical methodology — ICP triangulation, RFM segmentation, signal detection — that HubSpot's server doesn't include. They're complementary. Run both. Try it today — free, no API key needed: pip install artefact-mcp
GitHub: github.com/alexboissAV/artefact-mcp-server
PyPI: pypi.org/project/artefact-mcp/