README.md•5.49 kB
# Label Studio MCP Server
## Overview
This project provides a Model Context Protocol (MCP) server that allows interaction with a [Label Studio](https://labelstud.io/) instance using the `label-studio-sdk`. It enables programmatic management of labeling projects, tasks, and predictions via natural language or structured calls from MCP clients. Using this MCP Server, you can make requests like:
* "Create a project in label studio with this data ..."
* "How many tasks are labeled in my RAG review project?"
* "Add predictions for my tasks."
* "Update my labeling template to include a comment box."
<img src="./static/example.png" alt="Example usage of Label Studio MCP Server" width="600">
## Features
* **Project Management**: Create, update, list, and view details/configurations of Label Studio projects.
* **Task Management**: Import tasks from files, list tasks within projects, and retrieve task data/annotations.
* **Prediction Integration**: Add model predictions to specific tasks.
* **SDK Integration**: Leverages the official `label-studio-sdk` for communication.
## Prerequisites
1. **Running Label Studio Instance:** You need a running instance of Label Studio accessible from where this MCP server will run.
2. **API Key:** Obtain an API key from your user account settings in Label Studio.
## Configuration
The MCP server requires [the URL and API key for your Label Studio instance](https://labelstud.io/guide/access_tokens). If launching the server via an MCP client configuration file, you can specify the environment variables directly within the server definition. This is often preferred for client-managed servers.
Add the following JSON entry to your `claude_desktop_config.json` file or Cursor MCP settings:
```json
{
"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_actual_api_key_here", // <-- Your API key
"LABEL_STUDIO_URL": "http://localhost:8080"
}
}
}
}
```
<!--
## Installation
Follow these instructions to install the server.
```bash
git clone https://github.com/HumanSignal/label-studio-mcp-server.git
cd label-studio-mcp-server
# Install dependencies using uv
uv venv
source .venv/bin/activate
uv sync
```
```json
{
"mcpServers": {
"label-studio": {
"command": "uv",
"args": [
"--directory",
"/path/to/your/label-studio-mcp-server", // <-- Update this path
"run",
"label-studio-mcp.py"
],
"env": {
"LABEL_STUDIO_API_KEY": "your_actual_api_key_here", // <-- Your API key
"LABEL_STUDIO_URL": "http://localhost:8080"
}
}
}
}
```
When configured this way, the `env` block injects the variables into the server process environment, and the script's `os.getenv()` calls will pick them up. -->
## Tools
The MCP server exposes the following tools:
### Project Management
* **`get_label_studio_projects_tool()`**: Lists available projects (ID, title, task count).
* **`get_label_studio_project_details_tool(project_id: int)`**: Retrieves detailed information for a specific project.
* **`get_label_studio_project_config_tool(project_id: int)`**: Fetches the XML labeling configuration for a project.
* **`create_label_studio_project_tool(title: str, label_config: str, ...)`**: Creates a new project with a title, XML config, and optional settings. Returns project details including a URL.
* **`update_label_studio_project_config_tool(project_id: int, new_label_config: str)`**: Updates the XML labeling configuration for an existing project.
### Task Management
* **`list_label_studio_project_tasks_tool(project_id: int)`**: Lists task IDs within a project (up to 100).
* **`get_label_studio_task_data_tool(project_id: int, task_id: int)`**: Retrieves the data payload for a specific task.
* **`get_label_studio_task_annotations_tool(project_id: int, task_id: int)`**: Fetches existing annotations for a specific task.
* **`import_label_studio_project_tasks_tool(project_id: int, tasks_file_path: str)`**: Imports tasks from a JSON file (containing a list of task objects) into a project. Returns import summary and project URL.
### Predictions
* **`create_label_studio_prediction_tool(task_id: int, result: List[Dict[str, Any]], ...)`**: Creates a prediction for a specific task. Requires the prediction result as a list of dictionaries matching the Label Studio format. Optional `model_version` and `score`.
## Example Use Case
1. Create a new project using `create_label_studio_project_tool`.
2. Prepare a JSON file (`tasks.json`) with task data.
3. Import tasks using `import_label_studio_project_tasks_tool`, providing the project ID from step 1 and the path to `tasks.json`.
4. List task IDs using `list_label_studio_project_tasks_tool`.
5. Get data for a specific task using `get_label_studio_task_data_tool`.
6. Generate a prediction result structure (list of dicts).
7. Add the prediction using `create_label_studio_prediction_tool`.
## Contact
For questions or support, reach out via [GitHub Issues](https://github.com/HumanSignal/label-studio-mcp-server/issues).