
🤖 Human Use is the easiest way to connect your AI agents with human intelligence via the Rapidata API.
Finding the best slogan
Function Naming
Ranking different image generation models.
The MCP server is a tool that allows you to connect your AI agents with human intelligence via the Rapidata API.
- get_free_text_responses
- Will ask actual humans to provide some short free text responses to the question.
- get_human_image_classification
- Will ask actual humans to classify the images in the directory.
- get_human_image_ranking
- Will ask actual humans to rank the images in the directory.
- get_human_text_comparison
- Will ask actual humans to compare two texts and select which one is better.
Cursor
add the following to your cursor mcp.json file (usually in ~/.cursor/mcp.json)
{
"mcpServers": {
"human-use": {
"command": "uv",
"args": [
"--directory",
"YOUR_ABSOLUTE_PATH_HERE",
"run",
"rapidata_human_api.py"
]
}
}
}
You should now be able to see the human-use server in Cursor settings.
The app is a custom Streamlit app that allows you to use the MCP server. We have built because of issues with other clients. Namely the Claude desktop app.
Clone the following repositories along side the current one (do not clone them inside the current one, can be whereever it's convenient).:
git clone https://github.com/RapidataAI/human-use.git
- Create a .env file in the human-use repository
- Use the .env.example file as a template
- Replace the default values with your own credentials/settings
Note: paths should be ABSOLUTE paths
Install uv if you haven't already:
# For MacOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# For Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
- Create and activate a virtual environment:
uv venv # On Unix/macOS source .venv/bin/activate # On Windows .venv\Scripts\activate
- Install dependencies:
uv sync
streamlit run app.py
If you encounter issues, with the dependencies make sure that "which python" and "which streamlit" are the same path. If they are not the same path, run "python -m streamlit run app.py" instead of "streamlit run app.py".
If you have any questions or need further assistance, please contact us at info@rapidata.ai.