human-mcp

MCP server that provides humans as MCP tools

demo

overview

human-mcp is an MCP server that allows AI assistants to leverage human capabilities: it receives requests from AI assistants, displays instructions to humans, and returns responses from humans to the AI assistant.

Key features:

Accepts tool execution requests (via STDIN) from MCP clients
Write the instructions required for execution to a SQLite database
The Streamlit application monitors SQLite, displays instructions to the human, and prompts for responses.
Write the results of human input via Streamlit to SQLite
The MCP server reads the results from SQLite and returns them to the client (via STDOUT) as an MCP response.

Related MCP server: browser-use MCP Server

Tools provided

human_eye_tool : A human eye is used to describe a situation or locate something specific.
human_hand_tool : A human using his or her hand to perform a simple physical manipulation.
human_mouth_tool : A human uses his mouth to say the specified words.
human_weather_tool : A human checks and reports the weather in your location.
human_ear_tool : A human uses his ears to hear sounds and describe the situation.
human_nose_tool : A human uses their nose to identify smells.
human_taste_tool : A human uses his mouth to taste food and describe its taste.

set up

Prerequisites

Python 3.12 or higher
uv
SQLite3

Installation Instructions

Clone the repository
git clone https://github.com/yourusername/human-mcp.git cd human-mcp
Create and activate the virtual environment
uv venv source .venv/bin/activate
Install dependencies
uv pip install .

How to use

Install MCP server

task install-mcp

Connect to MCP server from Claude
"human-mcp": { "command": "uv", "args": [ "run", "--with", "mcp[cli]", "mcp", "run", "$PATH_TO_REPOSITORY/human_mcp/mcp_server.py" ] }
Launch Streamlit UI in a second terminal
task run-streamlit
Access the Streamlit UI in your browser (usually http://localhost:8501 )
Once you submit your request through your MCP client (e.g. Claude Desktop), the task will appear in the Streamlit UI.
Once you enter your response in the Streamlit UI and click the "Send Response" button, the response will be sent back to the MCP client.

Project Structure

human-mcp/ ├── human_mcp/ # メインのPythonパッケージ │ ├── __init__.py # パッケージマーカー │ ├── db_utils.py # SQLite関連ユーティリティ │ ├── tools.py # ツール定義 │ ├── mcp_server.py # MCPサーバー本体 │ └── streamlit_app.py # Streamlit UI アプリ ├── human_tasks.db # SQLite データベースファイル (実行時に生成) ├── pyproject.toml # プロジェクト設定、依存関係 └── README.md # このファイル

license

MIT

Notes

This project is intended for use as a joke. In actual operation, it is necessary to take into account the burden on human operators and response delays.