interactive-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| request_user_inputA | |
| message_complete_notificationA | |
| start_intensive_chatA | |
| ask_intensive_chatA | |
| stop_intensive_chatA |
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 5 tools
Most tools have distinct purposes: start/stop/ask_intensive_chat form a clear lifecycle for intensive chat sessions, message_complete_notification is for signaling completion, and request_user_input is for general pop-up prompts. However, ask_intensive_chat and request_user_input both ask questions to the user, which could cause some confusion about when to use each, though their contexts differ (session-based vs. standalone).
All tool names follow a consistent snake_case pattern with clear verb_noun structure: start_intensive_chat, ask_intensive_chat, stop_intensive_chat, message_complete_notification, request_user_input. The naming is predictable and readable throughout the set.
With 5 tools, this server is well-scoped for interactive user input scenarios. It covers the core needs: starting, managing, and stopping intensive chat sessions, sending standalone user prompts, and signaling completion. Each tool has a clear role without being overly complex or insufficient.
The tool set provides complete coverage for interactive user input workflows. It supports both intensive chat sessions (with start, ask, and stop tools) and standalone user prompts, plus a notification tool for completion signaling. There are no obvious gaps; agents can handle various interactive scenarios effectively.