Used as the persistent storage layer that manages the state of tasks between the AI assistant and human operators, storing instructions and responses.
Provides a user interface for humans to view tasks requested by the AI and submit responses, acting as the bridge between human operators and the AI assistant.
human-mcp
MCP server that provides humans as MCP tools
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.
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
- Create and activate the virtual environment
- Install dependencies
How to use
- Install MCP server
- Connect to MCP server from Claude
- Launch Streamlit UI in a second terminal
- 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
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.
This server cannot be installed
local-only server
The server can only run on the client's local machine because it depends on local resources.
An MCP server that allows AI assistants to utilize human capabilities by sending requests to humans and receiving their responses through a Streamlit UI.
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