A
licenseNot graded
qualityD
maintenanceEnables AI agents to query and interact with Azure DevOps data, including work items, projects, ticket statistics, and backlog information through natural language commands.
8,052 npm
MIT
Azure DevOps MCP Server
by OnoSendae
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TDQS
C2.9/5.0
Scored across 30 tools
Disambiguation4/5
Most tools are clearly separated by resource (work items, boards, iterations, PRs, teams, repos, wikis), but some overlap exists within work items (e.g., azure_get_work_item vs azure_query_work_items vs azure_get_my_tasks). Helpers like get_my_tasks and get_critical_bugs are essentially specialized queries, which could cause slight confusion.
Naming Consistency4/5
Tool names generally follow the verb_noun pattern (e.g., azure_create_work_item, azure_list_boards), but there are minor inconsistencies like azure_get_board_config vs azure_update_board (not update_board_config) and azure_get_work_item_states. Overall predictable but not perfectly uniform.
Tool Count2/5
With 30 tools, the server exceeds the recommended range and feels heavy. While it covers multiple Azure DevOps domains, many subdomains have only a few operations, making the high count unnecessary and potentially overwhelming.
Completeness3/5
Work items and wikis have decent lifecycle coverage, but other areas are incomplete: pull requests only support list/create (no get/update/merge), repositories have only list/get (no create/delete), and teams lack update/delete. These gaps will force agents to work around missing functionality.
Maintenance
ActivityInactive
ResponsivenessNo issues