A
licenseNot graded
qualityC
maintenanceEnables AI assistants to interact with RetainQ workspaces, including querying retention metrics, managing flows, analyzing churn data, and handling customers, offers, opportunities, and feedback.
3 npm
MIT
Retain MCP Server
Officialby retain-so
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TDQS
A4/5.0
Scored across 8 tools
Disambiguation5/5
Each tool targets a distinct aspect of churn management: customer lists by risk, individual customer profiles, MRR risk summary, active alerts, churn metrics, and alert actions (note, mark contacted, archive). No two tools have overlapping purposes, and descriptions clearly differentiate them.
Naming Consistency5/5
All read operations follow a consistent 'get_' prefix, while write operations use descriptive verb+nouns (add_customer_note, mark_alert_contacted, archive_alert). The naming is uniformly snake_case and predictable, making it easy for agents to infer tool behavior from names.
Tool Count5/5
With 8 tools, the set is well-scoped for a churn management server. It covers essential read operations (customer lists, details, metrics, alerts) and write operations (note, contacted, archive) without being bloated or insufficient. The count is appropriate for the domain.
Completeness4/5
The tool set covers the core workflow of identifying at-risk customers, monitoring alerts, and managing outreach states. Minor gaps exist, such as the inability to create or resolve alerts programmatically, but the available tools provide sufficient functionality for typical monitoring and action tasks.
Maintenance
ActivityStale
ResponsivenessNo issues