Customer context for AI agents
Ask your AI agent about customer health, usage, and churn risk without switching between tools.
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● get_at_risk_customers(risk_level: ["Critical", "High"]) ⎿ 7 customers7 accounts are slipping. The heaviest by MRR:CustomerRiskMRRHealthInactiveAcme IncCritical$1,2002418dGlobexCritical$9003112dInitechHigh$650449dUmbrellaHigh$480496dHooliHigh$420525d> ▋Ask about your customers. Give your AI agent access to customer health, usage, lifecycle, and churn risk.
Go beyond the dashboard. Let your AI agent connect customer signals and surface patterns that would take much longer to find manually.
Analyze your entire customer base. Compare accounts, spot common behaviors, and find the customers or patterns worth your attention.
Make AI useful for retention
Bring Retain’s customer data and retention signals into your AI client, so you can investigate accounts and work with alerts in natural language.
Whatever you already talk toClaude, Cursor, Codex, Gemini, Perplexity.
Everything it can callSeven tools. Five read, two touch alert state.
get_at_risk_customersreadget_customer_detailsreadget_mrr_at_riskreadget_active_alertsreadget_churn_metricsreadmark_alert_contactedwritearchive_alertwrite
Not every retention question needs a dashboard.
Some questions are worth an alert. Others are just things you want to know right now. Ask your AI agent, get the answer from Retain, and keep moving.
MCP, answered plainly.
What people ask before pointing an agent at their customer data.
Put your churn data in your agent today
Generate a key, paste one config block, and ask it who is leaving.
