Skip to main content
Glama

compose_config

Read-only

Render the canonical Docker Compose configuration after merges, profiles, and variable substitution. Validate compose files and preview the exact services and settings before running.

Instructions

Render the canonical compose configuration after merges, profiles, and variable substitution.

Use it to validate compose files and see exactly what the CLI will run before compose_up. Does not raise on a non-zero CLI exit: on a failed render config may be None — inspect raw.stderr.

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) project_name - Compose project name override profiles - Profiles to activate before rendering services_only - List service names only (--services) format - Render as YAML (default) or JSON returns: dict - {"config": str|dict|None, "raw": }; config is a parsed dict when format="json" and parsing succeeds, otherwise the rendered text from stdout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNo
formatNoyaml
profilesNo
project_dirNo
project_nameNo
services_onlyNo
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds valuable failure semantics: 'Does not raise on a non-zero CLI exit: on a failed render config may be None — inspect raw.stderr.' This goes beyond the structured annotations by explaining error behavior and return state.

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 focused purpose sentence, usage guidance, failure behavior, then an args list and return specification. Every section earns its place and there is no filler or redundant restatement of the tool name.

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 has no output schema, the description fully specifies the return dict shape: config as str/dict/None, raw as CliResult dict, and the parsing behavior for format='json'. Combined with parameter coverage and annotations, this is sufficiently complete for an agent to invoke and interpret results.

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's args section compensates fully with concise one-liners for all six parameters, including useful details like project_dir default/copy behavior, files repeatability, services_only mapping to --services, and format behavior. This adds meaning beyond the raw 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 opens with a specific verb and resource: 'Render the canonical compose configuration after merges, profiles, and variable substitution.' This clearly distinguishes compose_config as a read-oriented rendering/validation tool, not an operational Compose action like compose_up or compose_down.

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

Usage Guidelines4/5

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

It provides clear guidance: 'Use it to validate compose files and see exactly what the CLI will run before compose_up.' This gives a concrete when-to-use scenario, though it does not explicitly mention when not to use it or name alternatives to exclude.

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