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Human-In-the-Loop MCP Server

Human-In-the-Loop MCP Server

by GongRzhe
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_user_input

Opens a dialog box to request text, numbers, or other data from the user, enabling direct human input during AI tasks.

Instructions

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.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "title": "<title>",
      "prompt": "<prompt>"
    },
    "name": "get_user_input"
  }
}

Input Schema

NameRequiredDescriptionDefault
titleYesTitle of the input dialog window
promptYesThe prompt/question to show to the user
input_typeNoType of input expectedtext
default_valueNoDefault value to pre-fill in the input field

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It mentions opening a GUI dialog but does not explain blocking behavior, cancellation handling, or error states. Critical transparency for an interactive tool is missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise but contains slight redundancy (the third sentence repeats the idea of getting user input). The main purpose is front-loaded, but could be sharper.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and simple parameters, the description covers basic functionality. However, it omits behavioral details like modal vs non-modal, which are important for a dialog tool. Adequate but not thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema; it does not clarify the difference between integer and float input types or the purpose of default_value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates an input dialog for text, numbers, or other data. It distinguishes from siblings implicitly via input_type but does not explicitly contrast with get_multiline_input or get_user_choice.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use or when-not-to-use guidance is provided. The description says 'perfect for getting specific details' but does not mention alternatives or conditions. With sibling tools like get_multiline_input and get_user_choice, the lack of guidance is a significant gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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