Skip to main content
Glama

compose_pull

Pre-fetch container images for a Docker Compose project without starting services. Stage images before an outage window, refresh caches before compose_up, or verify registry access. Supports selective service pulls and ignores failures.

Instructions

Pre-fetch images for a compose project's services without starting them.

Use this to stage images before an outage window, to refresh cached images before compose_up, or to verify images are accessible without starting containers. For registry-authenticated pulls ensure the daemon is logged in first with system_login. compose_up --pull always does the same as part of startup; use this tool when you want to separate the pull step.

args: project_dir - Dir with the compose file (default: server cwd; copied to the target host if no local plugin) files - Explicit compose file paths (repeatable, -f; overrides auto-discovery) project_name - Override the compose project name services - Pull only these services; omit to pull all ignore_pull_failures - Continue if an individual image pull fails timeout_seconds - Subprocess timeout (default 1800s for large image pulls) returns: dict - {"returncode": int, "stdout": str, "stderr": str, "truncated": bool}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNo
servicesNo
project_dirNo
project_nameNo
timeout_secondsNo
ignore_pull_failuresNo
Behavior4/5

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

With annotations only providing readOnlyHint=false and destructiveHint=false, the description carries the burden of behavioral detail. It states that containers are not started, explains the project_dir copying behavior for remote hosts, and mentions ignore_pull_failures semantics and timeout default. It does not contradict annotations and adds useful context, though it could elaborate on failure modes beyond the return dict.

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 well-structured: a one-sentence purpose, then usage guidance, then a parameter list, then return value. Every sentence adds value—no filler. It is longer than average, but the added length is justified by the density of useful information.

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?

Despite no output schema, the description includes the return dict format, which covers expected results. It also provides parameter details, alternatives, and prerequisites. For a tool with 6 parameters and no schema coverage, this description is remarkably complete and leaves no major gaps.

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%, so the description must fully explain the 6 parameters. It does so: project_dir, files, project_name, services, ignore_pull_failures, and timeout_seconds each get a clear, schema-enriching explanation. This more than compensates for the lack of schema-level documentation.

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 opens with a specific action: 'Pre-fetch images for a compose project's services without starting them.' This clearly states the verb, resource, and scope, and distinguishes it from siblings like compose_up and image_pull by emphasizing the separation of pulling from startup.

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 gives explicit use cases ('stage images before an outage window', 'refresh cached images before compose_up', 'verify images are accessible without starting containers') and directly contrasts with compose_up --pull always, telling the agent when to prefer this tool. It also notes the prerequisite for registry-authenticated pulls (system_login).

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