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Label Studio MCP Server

@HumanSignal

Repository

Basic information

Category

Other

License

Apache-2.0

Transports

stdio

Author

HumanSignal

About Label Studio MCP Server

No overview available yet

#data-labeling#data-science

Label Studio MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "label-studio": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/HumanSignal/label-studio-mcp-server",
        "mcp-label-studio"
      ],
      "env": {
        "LABEL_STUDIO_API_KEY": "<YOUR_API_KEY>",
        "LABEL_STUDIO_URL": "<YOUR_LABEL_STUDIO_URL>"
      }
    }
  }
}

Label Studio MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list by running this server in a temporary sandbox using the button above.

Overview

What is Label Studio MCP Server?

Label Studio MCP Server is a Model Context Protocol (MCP) server that uses the official label-studio-sdk to allow programmatic management of Label Studio labeling projects, tasks, and predictions. It enables natural language or structured calls from MCP clients to interact with a Label Studio instance.

How to use Label Studio MCP Server?

Configure it by setting the LABEL_STUDIO_API_KEY and LABEL_STUDIO_URL environment variables. Add the server definition to your MCP client configuration (e.g., claude_desktop_config.json) using the uvx command and specify the required environment variables. Then invoke tools like create_label_studio_project_tool, import_label_studio_project_tasks_tool, and create_label_studio_prediction_tool through your MCP client.

Key features of Label Studio MCP Server

  • Project management: Create, update, list, and view project details/configurations.
  • Task management: Import tasks from files, list tasks, retrieve data and annotations.
  • Prediction integration: Add model predictions to specific tasks.
  • SDK integration: Leverages official label-studio-sdk for reliable communication.
  • Natural language interaction: Query project status and task counts via MCP clients.

Use cases of Label Studio MCP Server

  • Automated project setup: Create labeling projects with custom XML configs programmatically.
  • Bulk task import: Import thousands of tasks from a JSON file into a project in one step.
  • ML prediction injection: Add predictions from machine learning models to existing tasks.
  • Project status queries: Ask natural language questions like “How many tasks are labeled in my RAG review project?”.
  • Template updates: Update labeling configurations without manual UI navigation.

Frequently asked questions

1

What dependencies are required?

A running Label Studio instance accessible from the server, and an API key from your Label Studio user account. The server uses Python, `uv`, and the `label-studio-sdk`.

2

How do I configure authentication?

Set the `LABEL_STUDIO_API_KEY` environment variable to your Label Studio user account API key, and `LABEL_STUDIO_URL` to the URL of your Label Studio instance.

3

Where does my data live?

All data remains in your Label Studio instance. The server only reads from and writes to that instance via its API; it does not store data locally.

4

Are there any known limits?

Listing tasks returns up to 100 task IDs per call. The task import tool expects a JSON file containing a list of task objects. Predictions must follow the Label Studio format as a list of dictionaries.

5

What transport does the MCP server use?

The server is launched as a subprocess by the MCP client (e.g., via `claude_desktop_config.json`) and communicates over standard input/output using the MCP protocol.

Comments

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