Retain MCP Server
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- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to interact with RetainQ workspaces, including querying retention metrics, managing flows, analyzing churn data, and handling customers, offers, opportunities, and feedback.6 npmMIT
- AlicenseAqualityFmaintenanceConnects AI assistants to Custify customer success data for querying account metrics, health scores, and usage trends. It also supports taking actions such as creating notes, managing tasks, and triggering playbooks.1521 npm3MIT
- FlicenseBqualityAmaintenanceProvides access to Vitally customer success platform data, enabling users to search accounts and users, view health scores, manage conversations and tasks, and create notes through natural language interactions.111-
- AlicenseAqualityCmaintenanceEnables an AI assistant to answer customer-success questions by synthesizing simulated billing, support ticket, and product usage data into composite churn-risk scores, bands, and plain-language explanations for fictional accounts. It exposes raw-data tools, a synthesis tool, and a methodology resource so users can list at-risk accounts or get a per-account health summary.4MIT

Summit53 MCP Serverofficial
AlicenseNot gradedqualityCmaintenanceProvides 48 revenue intelligence tools that let AI assistants search deals, forecast revenue, analyze pipeline risk, manage outreach, and track value delivery via natural language.40 npm-- FlicenseBqualityDmaintenanceEnables interaction with Retell AI's voice and chat agent platform. Build, deploy, and manage AI phone agents, configure conversation flows, handle calls/chats, and manage phone numbers through natural language.52-
TDQS
Scored across 8 tools
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.
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.
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.
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.