Learn to build powerful cross-MCP workflows with Claude — 5 real production examples combining GitHub, Stripe, Sentry, Firecrawl, Supabase, and more.
Individual MCP servers are useful. But the real power emerges when you compose them — using the output of one server as the input to another, orchestrated by Claude's reasoning. This is where MCP transforms from a convenience into genuine AI automation.
The key insight: Claude maintains shared context across all connected MCPs in a session. Data flows naturally between servers without explicit integration code.
When a PR is merged to main, Claude uses the GitHub MCP to detect changed SQL files, extracts the migration statements, applies them via Supabase MCP, and commits the migration receipt back to the repository. Schema changes that used to require a developer on standby now run automatically with full audit trails.
See the full recipe: Auto DB Migrations on Push
Combines Stripe + Slack + GitHub.
A Stripe webhook fires when a payment fails. Claude reads the webhook payload via the Stripe MCP, enriches it with customer history, determines if it's a systemic issue (multiple failures in the same timeframe), posts a structured alert to Slack, and opens a GitHub issue if the failure rate exceeds a threshold. Three tools, one coherent workflow.
See the full recipe: Payment Failure Notifications
Combines GitHub + Playwright + Slack + Sentry.
A push triggers the GitHub Actions workflow. If Playwright tests fail, Claude reads the test output via GitHub MCP, checks Sentry for any related runtime errors that appeared around the same commit, writes a human-readable failure summary, and posts it to Slack with a direct link to the failing test video. This workflow eliminates the "reading CI logs" step entirely.
See the full recipe: Full CI Pipeline with Slack Alerts
Combines Firecrawl + Supabase + Slack.
Daily at 9am, Claude uses Firecrawl to scrape competitor pricing pages and product changelogs. It compares the extracted data against what's stored in Supabase from the previous day, identifies changes, and posts a structured diff to a Slack channel. Product and sales teams get automated competitive intelligence without any manual research.
See the full recipe: Scraping Pipeline to Supabase
Combines Sentry + Slack + GitHub.
Claude monitors your Sentry error budget in real time. When the error rate crosses a threshold, it posts to Slack with a summary of the top-occurring errors and creates GitHub issues with reproduction steps extracted from Sentry breadcrumbs. The workflow closes GitHub issues automatically when Sentry confirms the error rate has returned to baseline.
See the full recipe: Sentry Error Alerting
The pattern is always the same: trigger → enrich → act → report. Start with the trigger (a webhook, a cron job, or a Claude prompt), identify which MCPs hold the data you need, define what action to take, and choose how to report the outcome. Claude handles all the data plumbing between servers.
Browse all workflow recipes on the Recipes page to find pre-built templates for your stack.