MCP & Claude Skills, Part 2: How to Turn Discovery into Reusable Actions

Combining Connect AI’s Model Context Protocol server with Claude Skills enables users to turn exploratory, cross-system data queries into reusable automations within Claude Code, potentially reducing repeated schema discovery and token use. Using a customer-health example that joins Salesforce revenue data with Zendesk open-ticket counts, the workflow begins with Claude using MCP to inspect available schemas, identify relationships, generate SQL, and return results. The validated query is then packaged as a Claude Skill through metadata, a Python script that authenticates with Connect AI and executes the query, dependency specifications, and environment-variable templates. When similar questions are asked later, Claude Code can recognize the Skill’s trigger conditions, run the script, parse its JSON output, and present the findings in natural language. The approach assigns MCP to data exploration, Skills to repeatable execution, Claude to coordination, and Connect AI to governed enterprise connectivity, avoiding external schedulers or third-party automation.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.