Labelbox is a data labeling and annotation platform that enables teams to prepare high-quality training data for machine learning models. It provides tools for image, text, video, and document annotation with collaboration features and quality management.
13 of 33 checks passed. 14 unscored.
Can an agent find and understand this tool without a web search?
Can an agent create an account and get credentials without human intervention?
Can an agent operate autonomously without upfront payment or contracts?
How well does the API work for non-human consumers?
Does the tool fail gracefully when an agent makes a mistake?
Labelbox has an OpenAPI specification and sandbox environment, which aids discoverability somewhat, but lacks an MCP server and llms.txt file. The API is reasonably well-documented for querying and managing labeling projects, though agent tooling could be more comprehensive for automation workflows. Account creation requires manual signup without programmatic options. The platform is reliable with good uptime, but the free tier is limited and agent autonomy would be constrained by auth requirements and potential rate limits on the API.
Install the Agent Native Registry MCP server. Your agents can search, compare, and score tools mid-task.
claude mcp add --transport http agent-native-registry https://agentnativeregistry.com/api/mcp