Labellerr MCP Server
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TDQS
Scored across 22 tools
Several tools have overlapping purposes: dataset_get and query_dataset_info both retrieve dataset details, while monitor_project_progress and query_project_statistics both provide project progress stats. project_list and query_search_projects also overlap in listing projects. This creates ambiguity for agents selecting the right tool.
Naming is grouped by prefixes like project_, dataset_, annotation_, monitor_, query_, but the convention varies: some groups use resource_first (project_list, dataset_get) while others use action_first (monitor_job_status, query_project_statistics). Within each group it's consistent, but across groups the pattern is mixed, making it moderately predictable.
With 22 tools, the count is on the heavier side. The scope covers projects, datasets, annotations, monitoring, and queries, so it isn't unreasonable, but it's borderline compared to the typical 3-15 tool range for a well-scoped server. Some tools are redundant, further padding the count.
The server covers core workflows for projects, datasets, and annotations, including creation, retrieval, uploading, and export. However, it lacks basic delete operations (e.g., no project delete or dataset delete) and has no annotation listing or detailed annotation viewing. The duplication of dataset info and project stats tools also suggests incomplete integration of the query and monitor groups.