Chartcastr Engineering
Engineering team
Engineers writing about the integrations, AI patterns, and infrastructure that power Chartcastr.
The Chartcastr engineering team writes deep-dives on the systems that move data from sources to Slack — auth flows, AI insight generation, MCP servers, and the rendering pipeline that turns rows into charts.
Writes about
- MCP (Model Context Protocol)
- OAuth integrations
- AI insights
- chart rendering
- BigQuery
- webhook architecture
Elsewhere
Posts by Chartcastr Engineering
How to Connect Google Sheets and Schedule It to Slack
Connect a Google Sheet, pick a chart, choose a Slack channel, and set a schedule — your report posts itself daily, weekly, or monthly with an AI summary. Full step-by-step guide.
Schedule Google Sheets to Slack Without Zapier or Apps Script
You do not need Zapier, Apps Script, or a webhook to schedule a Google Sheets chart to Slack. Here is the no-code way to connect a sheet and have the report post itself — plus an honest comparison of the alternatives.
Automate a Recurring Google Sheets Summary in Slack with AI
A scheduled Google Sheets chart in Slack is better when it comes with a written summary of what changed. Here is how to automate a recurring chart-plus-AI-summary from a sheet to a Slack channel.
How domain expertise changes AI analysis: Shopify vs. HubSpot vs. Google Search Console
The same AI model produces fundamentally different output when it has domain-specific knowledge. Here is what that looks like across three real data sources.
MCP for analysts: connecting Chartcastr to Claude Code, Cursor, and ChatGPT
A practical guide to using the Model Context Protocol for ad-hoc analytics — what MCP is, how the Chartcastr MCP server works, three setup walkthroughs, and five example prompts that actually work.
