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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

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
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
run_containerA

Runs a Docker container locally for testing Args: image: Docker image to run, e.g. "nginx:latest" If no tag is specified, then usel alpine for default.It is smaller and faster to pull container_name: container name container_port: port the app listens on INSIDE the container, e.g. "80" for nginx host_port: port on your machine to access it, e.g. "8080" → http://localhost:8080

stop_containerC

User will pass the container name that we need to stop Args: container_name: Docker Container name

list_containersB

Returns all containers with their status

delete_containerA

Delete a container by its name. Stops it first if it's still running. Args: container_name: Container name that should be deleted

container_logsB

Collect and display the logs for a container Args: container_name: Container name to collect logs tail: Number of log lines to return (default 200)

container_restartD

Restarting a container Args: container_name: name to restart the container

container_startC

Starting a container Args: container_name: name to start the container

container_statsA

Shows live CPU and memory usage for a running container. Args: container_name: Docker Container name

container_inspectA

Returns detailed information about a container: environment variables, mounts, network IP, and health status. Args: container_name: Docker Container name

container_execB

Executes a shell command inside a running container and returns its output. Args: container_name: Docker Container name command: shell command to run inside the container, e.g. "ls -la /app"

deploy_stackA

Deploys a multi-container application from a docker-compose YAML definition. Args: project_name: unique name for this stack, used to group/manage its containers compose_yaml: full contents of a docker-compose.yml describing the services

stop_stackA

Stops all containers in a compose stack without removing them, so it can be started again later. Args: project_name: unique name for this stack, used to group/manage its containers

remove_stackA

Stops and permanently removes a compose stack: containers, networks, and volumes (data is deleted). Args: project_name: unique name for this stack, used to group/manage its containers

list_stacksA

Lists all compose projects, including stopped ones

stack_statusA

Shows the status of all containers in a compose stack (like docker compose ps). Args: project_name: unique name for this stack, used to group/manage its containers

stack_logsA

Collects logs from all containers in a compose stack. Args: project_name: unique name for this stack, used to group/manage its containers tail: number of log lines to return per container (default 200)

list_imagesA

List all Docker images

delete_imageA

Delete a Docker image by tag or ID. Removed even if still referenced by a stopped container (force). Args: image_name: image name to be deleted

build_imageA

Builds a Docker image from a Dockerfile already saved on disk. The build context is the folder containing the Dockerfile, so COPY/ADD of other files in that same folder works normally. Accepts either a Windows path ("C:\path\Dockerfile") or a Git Bash style path ("/c/path/Dockerfile"). Args: image_tag: tag to give the built image, e.g. "my-app:latest" dockerfile_path: full path to an existing Dockerfile on this machine

push_imageA

Tags a local Docker image with a registry repository name and pushes it (e.g. Docker Hub, AWS ECR). Requires that you have already run docker login locally — this tool does not accept credentials. Args: local_image: the image currently on your machine, e.g. "my-app:latest" repository: full destination repository name, e.g. "myusername/my-app" or "123456789012.dkr.ecr.eu-west-1.amazonaws.com/my-app" image_tag: tag to push, e.g. "latest" or "v1.0"

list_volumesA

Lists all Docker volumes with their driver and mountpoint

remove_volumeA

Deletes a Docker volume by name. Data stored in it is permanently lost. Fails if the volume is currently in use by a container. Args: volume_name: name of the volume to remove

list_networksA

Lists all Docker networks with their driver and scope

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.4/5.0

Scored across 23 tools

Disambiguation5/5

Each tool targets a distinct Docker operation (image build, container exec, stats, logs, stack management, etc.), with clear descriptions that prevent confusion. The only potential overlap is between container_start and run_container, but descriptions clarify that one starts an existing container and the other creates and starts a new one.

Naming Consistency3/5

Naming conventions are mixed: some tools use verb_noun (build_image, delete_container), others use noun_verb (container_exec, container_inspect), and list tools use list_noun. While individually readable, the lack of a unified pattern (e.g., all verb_noun or all noun_verb) makes it harder to predict tool names.

Tool Count4/5

With 23 tools covering images, containers, volumes, networks, and stacks, the number is appropriate for a Docker management server. It's comprehensive but not overwhelming, though a few tools (like list_networks and list_volumes) could be merged without loss of clarity.

Completeness4/5

Core Docker workflows are well-covered: building/pushing images, running/executing/inspecting containers, managing stacks. However, missing network creation/removal and volume creation mean agents may hit dead ends when trying to set up isolated test environments.

Maintenance

ActivitySlowing
ResponsivenessNo issues