cutie-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CUTIE_API_KEY | Yes | Admin API key (ck_live_...) | |
| CUTIE_API_URL | No | API base URL (default: https://api.cuti-e.com) | https://api.cuti-e.com |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_conversationsC | List conversations with optional filters. Returns conversations with status, priority, unread counts, and pagination. |
| get_conversationB | Get a single conversation with its messages and tags. |
| send_replyC | Send a reply message in a conversation. Can be a visible reply or an internal note. |
| update_conversationC | Update conversation status, priority, assignment, title, or category. |
| delete_conversationC | Close/delete a conversation. |
| list_appsB | List all registered apps for the current team, with usage stats. |
| get_appC | Get details for a specific app including configuration and notification settings. |
| get_dashboardC | Get analytics dashboard with conversation stats, response times, breakdowns by category/status/priority/app, daily trends, and team activity. |
| list_teamB | List all team members with their roles. |
| get_customerB | Get current team/customer info including tier, mascot settings, and brand color. |
| get_active_usersA | Get active user count (DAU/WAU/MAU) for a specific app based on anonymous activity pings. |
| get_active_users_all_appsC | Get active user counts across all apps at once. Queries each app's DAU/WAU/MAU stats. |
| get_sentiment_insightsC | Get sentiment analysis breakdown (positive/neutral/negative) by app, category, and time period. Powered by AI classification. |
| get_feature_requestsB | Get AI-extracted feature requests ranked by vote count. Each request is auto-extracted from user feedback and de-duplicated. |
| update_feature_requestC | Update the status or title of a feature request. |
| merge_feature_requestsA | Merge a duplicate feature request into a target. Combines vote counts and linked conversations, then deletes the source. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 16 tools
Most tools have distinct purposes targeting specific resources like conversations, apps, users, or feature requests, with clear separation between get/list operations. However, some potential overlap exists between 'get_dashboard' (analytics overview) and other specific analytics tools like 'get_active_users' or 'get_sentiment_insights', which could cause minor confusion about which to use for detailed metrics.
Tool names follow a highly consistent verb_noun pattern throughout, using clear action verbs like get, list, update, delete, send, and merge paired with specific nouns. All names use snake_case uniformly, making them predictable and easy to parse for an agent.
With 16 tools, the count is slightly on the higher side but reasonable for a customer support/analytics domain that covers conversations, apps, users, dashboards, and feature requests. It provides comprehensive functionality without being overwhelming, though it borders on feeling heavy compared to more focused servers.
The toolset offers excellent coverage for a customer support platform, including full CRUD/lifecycle operations for conversations (list, get, update, delete, send_reply), apps (list, get), feature requests (get, update, merge), and analytics (dashboard, active users, sentiment). No obvious gaps are present, enabling agents to handle end-to-end workflows effectively.