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Create service

createService

Provision a database, cache, or Docker Compose service on your Coolify server. Specify project_uuid, server_uuid, and environment, plus docker_compose_raw for compose deployments.

Instructions

Create a one-click service (database, cache, etc.) or a Docker Compose deployment (pass docker_compose_raw with the YAML content). Requires project_uuid, server_uuid, and environment_name (or environment_uuid). Since Coolify v4.1, Docker Compose deployments are services, not applications.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
typeNo
urlsNo
descriptionNo
server_uuidYes
project_uuidYes
instant_deployNo
destination_uuidNo
environment_nameNo
environment_uuidNo
docker_compose_rawNo
force_domain_overrideNo
is_container_label_escape_enabledNo
Behavior3/5

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

Annotations already declare this as a write operation (readOnlyHint=false) and non-destructive (destructiveHint=false), so the safety profile is covered. The description adds value by explaining the Docker Compose mode and version-specific behavior, but it does not disclose side effects, asynchronous deployment behavior, or return format, which would be useful given no output 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 two concise, front-loaded sentences. The first states the action and modes, the second adds requirements and a version note. No filler or redundant information; every sentence earns its place.

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

Completeness3/5

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

For a tool with 13 parameters and no output schema, the description is adequate but incomplete. It covers core purpose and required params, but lacks detail on many optional parameters and what the tool returns. The annotations help with safety, but return value and post-creation behavior are absent, making full autonomous invocation challenging.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It explains docker_compose_raw and clarifies the requirement/alternative for environment_name vs environment_uuid, but only touches 5 of 13 parameters. Many important parameters like type, instant_deploy, destination_uuid, and urls remain unexplained, leaving agents to guess their semantics.

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 clearly states the tool's purpose with a specific verb and resource: 'Create a one-click service (database, cache, etc.) or a Docker Compose deployment'. It also distinguishes itself from sibling tools by noting that since Coolify v4.1, Docker Compose deployments are services, not applications, which prevents confusion with createApplication.

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 context for when to use: for one-click services or Docker Compose deployments, and implicitly indicates not to use for applications post-v4.1. However, it does not explicitly name alternative tools (e.g., createDatabase) or state exclusions, leaving some ambiguity for edge cases.

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

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