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create_service

Create an app, database, or compose service in a Tugport project by supplying the project, name, and spec, enabling deployment and management from an AI agent.

Instructions

Create a service in a project. kind is app, database or compose. For apps pass spec.source ({type: git, repo, branch} | {type: image, image} | {type: dockerfile, content}); for databases pass database: {engine: postgres|mysql|mariadb|mongo|redis}.

Input Schema

NameRequiredDescriptionDefault
envNoInitial env vars {NAME: value}
kindNoapp, database or compose
nameYesService name
specNoService spec (see docs/API.md)
projectYesProject id or name
databaseNo{engine, user?, database?}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description bears the full burden. It never states whether creation triggers a deploy, requires specific permissions, is idempotent, or what happens on conflict — all important for a mutation tool with zero annotation coverage.

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

Conciseness4/5

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

Two tight sentences, front-loaded with the action, then the kind and per-kind payload guidance. Little waste, though the compressed brace-notation is dense to parse.

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

Completeness4/5

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

For a 6-param tool with nested objects and no output schema, the description covers the two most complex parameters (spec.source, database) well. Gaps remain around the compose kind and creation side effects, but the core call path is clear.

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

Parameters4/5

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

Schema coverage is 100%, but the schema only says 'Service spec (see docs/API.md)', so the description adds real value by spelling out the spec.source union shapes ({type: git...}, image, dockerfile) and the database engine enum. This meaningfully compensates beyond the schema's pointer to external docs.

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

Purpose4/5

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

The description opens with a specific verb+resource ('Create a service in a project') and clarifies the kind dimension. It doesn't explicitly contrast with update_service/delete_service, but the create verb and kind detail make intent unambiguous.

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

Usage Guidelines3/5

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

It gives conditional routing ('for apps pass spec.source...; for databases pass database...'), which helps select the right parameter path. However, there's no explicit when-to-use-this-vs-alternatives or when-not guidance against siblings like update_service or create_project.

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