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Glama
1sarthakbhardwaj

Labellerr MCP Server

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LOG_LEVELNoLog level for debugging (e.g., debug)info
LABELLERR_API_KEYYesYour Labellerr API key
LABELLERR_CLIENT_IDYesYour Labellerr client ID
LABELLERR_API_SECRETYesYour Labellerr API secret

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}
resources
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
project_createB

Create a new annotation project with dataset and guidelines

project_listA

List all projects for the client

project_getA

Get detailed information about a specific project

project_update_rotationB

Update rotation configuration for a project

dataset_createB

Create a new dataset

dataset_upload_filesC

Upload individual files to a dataset

dataset_upload_folderB

Upload all files from a folder to a dataset

dataset_listA

List all datasets (linked and unlinked)

dataset_getC

Get detailed information about a dataset

annotation_upload_preannotationsA

Upload pre-annotations to a project (synchronous)

annotation_upload_preannotations_asyncB

Upload pre-annotations to a project (asynchronous)

annotation_exportC

Create an export of project annotations

annotation_check_export_statusC

Check the status of export jobs

annotation_download_exportA

Get download URL for a completed export

monitor_job_statusC

Monitor the status of a background job

monitor_project_progressC

Get progress statistics for a project

monitor_active_operationsA

List all active operations and their status

monitor_system_healthA

Check the health and status of the MCP server

query_project_statisticsC

Get detailed statistics for a project

query_dataset_infoC

Get detailed information about a dataset

query_operation_historyC

Query the history of operations performed

query_search_projectsB

Search for projects by name or type

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
Operation HistoryHistory of all operations performed

TDQS

C2.9/5.0

Scored across 22 tools

Disambiguation2/5

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 Consistency3/5

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.

Tool Count3/5

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.

Completeness3/5

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.

Maintenance

ActivityInactive
ResponsivenessNo issues