docker-mcp
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- FlicenseNot gradedqualityDmaintenanceEnables AI assistants to manage Docker containers and images, including starting, stopping, listing, and building operations.2-
- AlicenseNot gradedqualityDmaintenanceEnables natural language management of Docker containers, images, networks, and volumes with support for both local and remote Docker engines. Features automated container composition, debugging capabilities, and persistent data management through an intuitive conversational interface.GPL 3.0
TDQS
Scored across 43 tools
Core resource operations are clearly scoped (list/inspect/create/remove for containers, images, volumes, networks), and compose/lab variants name their target explicitly. The parallel exec/log/up tools across container, compose, and lab contexts are distinct by scope, though an agent must know which context applies to avoid misselection.
Most tool names are snake_case with predictable verb_noun patterns for core resources (list_containers, inspect_image, remove_volume). Deviations exist for domain-prefixed compose/lab tools (compose_up, lab_exec) and a few noun-first info tools (container_logs, server_info, disk_usage), so the set is coherent but not uniformly verb_noun.
43 tools is well above the 15-tool guideline and even beyond the 25-tool 'too many' threshold. While Docker is broad, many operations (separate list/inspect per resource, parallel compose/lab suites) could be consolidated.
The surface covers CRUD/lifecycle for containers, images, volumes, networks, Compose, and labs, including exec, logs, and copying. Minor gaps remain (image push, network connect/disconnect, container update), but agents can work around them.