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MCP-Human: Human Assistance for AI Assistants

A Model Context Protocol (MCP) server that enables AI assistants to get human input when needed. This tool creates tasks on Amazon Mechanical Turk that let real humans answer questions from AI systems. While primarily a proof-of-concept, it demonstrates how to build human-in-the-loop AI systems using the MCP standard. See limitations for current constraints.

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Setup

Prerequisites

Configuring AWS credentials

# Configure AWS credentials for profile mcp-human
export AWS_ACCESS_KEY_ID="your_access_key"
export AWS_SECRET_ACCESS_KEY="your_secret_key"
aws configure set aws_access_key_id ${AWS_ACCESS_KEY_ID} --profile mcp-human
aws configure set aws_secret_access_key ${AWS_SECRET_ACCESS_KEY} --profile mcp-human

Configuring MCP server with your MCP client

Claude code

Sandbox mode:

claude mcp add human -- npx -y mcp-human@latest

The server defaults to sandbox mode (for testing). If you want to submit real requests, use MTURK_SANDBOX=false.

claude mcp add human -e MTURK_SANDBOX=false -- npx -y mcp-human@latest

Generic

Update the configuration of your MCP client to the following:

{
  "mcpServers": {
    "human": {
      "command": "npx",
      "args": ["-y", "mcp-human@latest"]
    }
  }
}

e.g.: Claude Desktop (MacOS): ~/Library/Application\ Support/Claude/claude_desktop_config.json

Related MCP server: AskMeMCP

Configuration

The server can be configured with the following environment variables:

Variable

Description

Default

MTURK_SANDBOX

Use MTurk sandbox (true) or production (false)

true

AWS_REGION

AWS region for MTurk

us-east-1

AWS_PROFILE

AWS profile to use for credentials

mcp-human

DEFAULT_REWARD

The reward amount in USD.

0.05

FORM_URL

URL where the form is hosted. Needs to be https.

https://syskall.com/mcp-human/

Setting Up AWS User with Mechanical Turk Access

To create an AWS user with appropriate permissions for Mechanical Turk:

  1. Log in to the AWS Management Console:

  2. Create a new IAM User:

    • Navigate to IAM (Identity and Access Management)

    • Click "Users" > "Create user"

    • Enter a username (e.g., mturk-api-user)

    • Click "Next" to proceed to permissions

  3. Set Permissions:

    • Choose "Attach existing policies directly"

    • Search for and select AmazonMechanicalTurkFullAccess

    • If you need more granular control, you can create a custom policy with specific MTurk permissions

    • Click "Next" and then "Create user"

  4. Create Access Keys:

    • After user creation, click on the username to go to their detail page

    • Go to the "Security credentials" tab

    • In the "Access keys" section, click "Create access key"

    • Choose "Application running outside AWS" or appropriate option

    • Click through the wizard and finally "Create access key"

  5. Save Credentials:

    • Download the CSV file or copy the Access key ID and Secret access key

    • These will be used as AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables

    • Important: This is the only time you'll see the secret access key, so save it securely

  6. Configure MTurk Requester Settings:

Note: Always start with the MTurk Sandbox (MTURK_SANDBOX=true) to test your integration without spending real money. Only switch to production when you're confident in your implementation.

Architecture

This system consists of two main components:

  1. MCP Server: A server implementing the Model Context Protocol that integrates with MTurk

  2. Form: A static HTML form.

The AI assistant connects to the MCP server, which creates tasks on MTurk. Human workers complete these tasks through a form, and their responses are made available to the AI assistant.

The Mechanical Turk form used is hosted on GitHub pages: https://syskall.com/mcp-human/. It gets populated with data through query parameters.

MCP Tools

askHuman

Allows an AI to ask a question to a human worker on Mechanical Turk.

Parameters:

  • question: The question to ask a human worker

  • reward: The reward amount in USD (default: $0.05)

  • title: Title for the HIT (optional)

  • description: Description for the HIT (optional)

  • hitValiditySeconds: Time until the HIT expires in seconds (default: 1 hour)

Example usage:

// From the AI assistant's perspective
const response = await call("askHuman", {
  question:
    "What's a creative name for a smart home device that adjusts lighting based on mood?",
  reward: "0.25",
  title: "Help with creative product naming",
  hitValiditySeconds: 3600, // HIT valid for 1 hour
});

If a worker responds within the HIT's validity period, the response will contain their answer. If not, it will return a HIT ID that can be checked later.

checkHITStatus

Check the status of a previously created HIT and retrieve any submitted assignments.

Parameters:

  • hitId: The HIT ID to check status for

Example usage:

// From the AI assistant's perspective
const status = await call("checkHITStatus", {
  hitId: "3XMVN1BINNIXMTM9TTDO1GKMW7SGGZ",
});

Resources

mturk-account

Provides access to MTurk account information.

URIs:

  • mturk-account://balance - Get account balance

  • mturk-account://hits - List HITs

  • mturk-account://config - Get configuration info

Limitations

  • Need to implement progress notifications to avoid getting timing out.

  • Currently only supports simple text-based questions and answers

  • Limited to one assignment per HIT

  • No support for custom HTML/JS in the form

  • Simple polling for results rather than a webhook approach

  • Uses MTurk's ExternalQuestion format, which requires hosting a form

Available Tools

2 tools
askHumanD
ParametersJSON Schema
NameRequiredDescriptionDefault
questionYesThe question to ask a human worker
rewardNoThe reward amount in USD (default: $0.05)0.05
titleNoTitle for the HIT (optional)
descriptionNoDescription for the HIT (optional)
hitValiditySecondsNoTime until the HIT expires in seconds (default: 1 hour)

TDQS

D1/5.0
Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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

Completeness1/5

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

Tool has no description.

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

Parameters1/5

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

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

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

checkHITStatusD
ParametersJSON Schema
NameRequiredDescriptionDefault
hitIdYesThe HIT ID to check status for

TDQS

D1/5.0
Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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

Completeness1/5

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

Tool has no description.

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

Parameters1/5

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

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 2 tool updatesv0.0.6
    • First observedaskHuman
    • First observedcheckHITStatus

TDQS

D1.6/5.0

Scored across 2 tools

Disambiguation3/5

The two tools have distinct names suggesting different functions (asking vs. checking status), but without descriptions, an agent may not fully grasp their specific roles or parameters, leading to potential confusion.

Naming Consistency4/5

Both tool names follow a camelCase pattern with verb-first structure (askHuman, checkHITStatus), though 'HIT' is capitalized, which is acceptable for an acronym. Overall, naming is clear and consistent.

Tool Count3/5

With only 2 tools, the server feels minimal for a domain centered on human interaction. It could be acceptable for a very narrow purpose, but likely leaves users wanting more functionality.

Completeness2/5

The tool set covers only asking a human and checking status of a HIT, but lacks essential operations like creating, updating, or listing HITs. This creates significant gaps for typical interaction workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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