Skip to main content
Glama

volume_create

Create a Docker volume for persistent data storage, supporting custom drivers, labels, and driver options. Use named volumes for critical data, anonymous for temporary use.

Instructions

Create a volume managed by Docker.

Named volumes persist after their containers stop or are removed; use them for databases, uploads, or any data that must outlive a container. Anonymous volumes (no name) are only removed automatically when the container was started with --rm or removed with docker rm -v; otherwise they accumulate and must be pruned manually. Common driver_opts for the default local driver: bind-mount an existing host path with {"type": "none", "device": "/host/path", "o": "bind"}, or mount an NFS share with {"type": "nfs", "device": "server:/export", "o": "addr=server,rw"}. Third-party drivers (e.g. rexray, convoy) accept their own option keys. List existing volumes with volume_list; reclaim unused ones with volume_prune. Created volumes are stamped with provenance labels.

args: name - Volume name; auto-generated if omitted (creates an anonymous volume) driver - Volume driver to use (default: "local") driver_opts - Driver-specific options dict labels - Labels to set on the volume returns: dict - The created volume's attrs ({"Name", "Driver", "Mountpoint", "Labels", ...})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
driverNo
labelsNo
driver_optsNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

While annotations indicate the tool is not read-only and not destructive, the description adds significant behavioral context: the lifecycle differences between named and anonymous volumes, the '--rm' and 'docker rm -v' removal caveat, and the fact that volumes are 'stamped with provenance labels.' These details are not available in the annotations or schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than average, but every sentence provides necessary information: use cases, lifecycle caveats, driver option examples, related tools, and return format. It is well-structured in paragraphs and not repetitive, earning its length without fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 parameters, nested objects, no output schema), the description is complete. It covers purpose, parameter semantics, driver options, lifecycle behaviors, related tools, and return value shape. The agent has everything needed to invoke the tool correctly without guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates by explaining each parameter in context: 'name' determines anonymous vs. named volume, 'driver' defaults to 'local', and 'driver_opts' includes concrete examples for bind mounts and NFS. It also documents the return value structure, which is not in an output schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with a clear, specific statement: 'Create a volume managed by Docker.' It distinguishes this from related volume tools by explaining when anonymous vs. named volumes are appropriate, making the purpose unambiguous and distinct from volume_list, volume_prune, and volume_remove.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states use cases: 'use them for databases, uploads, or any data that must outlive a container.' It also provides alternative actions: 'List existing volumes with volume_list; reclaim unused ones with volume_prune.' This goes beyond a simple usage hint and tells the agent when to use this tool versus related operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/L337-org/docker-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server