ITM Platform MCP Server
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- FlicenseNot gradedqualityDmaintenanceEnables AI assistants to interact with OpenProject installations for comprehensive project management, including creating projects and work packages, managing users and assignments, creating dependencies, and generating Gantt charts through natural language commands.15-
- AlicenseBqualityBmaintenanceEnables AI assistants to read and update Taiga projects — epics, user stories, tasks, issues, sprints, comments, and wiki pages — using natural language.70121 npm3MIT
- FlicenseNot gradedqualityDmaintenanceEnables AI assistants like Claude to create and manage projects, todos, priorities, and statuses through natural language, bridging the gap between AI and project management workflows.-
- FlicenseNot gradedqualityNot gradedmaintenanceEnables AI assistants to interact with Rytnow project management platform, supporting task management, time tracking, plan creation, and team collaboration through natural language commands.-
- AlicenseNot gradedqualityCmaintenanceProvides AI tools with secure, real-time, permission-aware access to an Orangescrum workspace so users can search, create, and update projects, tasks, sprints, test cases, releases, risks, resources, and Wiki pages through natural language. It lets assistants summarize and plan work, automate repetitive effort, and keep delivery data current without switching context.3Apache 2.0
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to interact with Implem.Pleasanter project management systems, supporting issue management, advanced search, analytics, bulk operations, and team productivity insights through natural language.7MIT
TDQS
Scored across 47 tools
Most tools target clear resource+action pairs and the descriptions explicitly clarify boundaries, such as list_project_tasks vs search_tasks vs get_task, and create_task_progress vs update_task_progress vs update_task. The main ambiguity comes from query_datamart and aggregate_portfolio, which overlap conceptually with typed reporting tools, but they are positioned as advanced/analytics escape hatches.
Tool names consistently use snake_case verb_noun patterns such as search_projects, get_project, create_task, update_risk, list_task_progress, and bulk_update_task_status. Variations like search vs list vs get are used semantically and remain predictable across the large surface.
With 47 tools, the surface is very heavy for an agent to navigate reliably. The domain is broad enough to justify many tools, but this count exceeds a comfortable scoped set and increases selection cost and maintenance complexity.
Coverage is strong across projects, services, tasks, risks, issues, activities, progress, effort, time entry, budgets, custom fields, users, and DataMart queries. The notable gaps are the absence of explicit delete/archive operations and read-only coverage for purchases/revenues, though many lifecycle needs can be handled through status updates or related write tools.