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animalnots

Human-In-the-Loop MCP Server

by animalnots

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
HITL_DEBUGNoEnable debug logging. Set to 1 to enable.

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": true
}
logging
{}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
extensions
{
  "io.modelcontextprotocol/ui": {}
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_user_inputB

Create an input dialog window for the user to enter text, numbers, or other data.

This tool opens a GUI dialog box where the user can input information that the LLM needs. Perfect for getting specific details, clarifications, or data from the user.

get_user_choiceB

Create a choice dialog window for the user to select from multiple options.

This tool opens a GUI dialog box with a list of choices where the user can select one or multiple options. Perfect for getting decisions, preferences, or selections from the user.

get_multiline_inputA

Create a multi-line text input dialog for the user to enter longer text content.

This tool opens a GUI dialog box with a large text area where the user can input multiple lines of text. Perfect for getting detailed descriptions, code, or long-form content.

show_confirmation_dialogA

Show a confirmation dialog with Yes/No buttons.

This tool displays a message to the user and asks for confirmation. Perfect for getting approval before proceeding with an action.

show_info_messageA

Show an information message to the user.

This tool displays an informational message dialog to notify the user about something. The user just needs to click OK to acknowledge the message.

health_checkA

Check if the Human-in-the-Loop server is running and GUI is available.

Prompts

Interactive templates invoked by user choice

NameDescription
get_human_loop_promptGet prompting guidance for LLMs on when and how to use human-in-the-loop tools. This tool returns comprehensive guidance that helps LLMs understand when to pause and ask for human input, decisions, or feedback during task execution.

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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