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fredericsuretat

Docker Forge MCP

generate_stack

Transform natural language descriptions into production-ready Docker Compose stacks, including security best practices and optional Traefik reverse proxy configuration.

Instructions

Generate a production-ready Docker Compose stack from a natural language description or stack type. Includes security best practices: resource limits, healthchecks, restart policies, non-root users, named volumes. Optionally adds Traefik v3 labels for reverse proxy + HTTPS.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainNoPublic domain for Traefik routing, e.g. "myapp.example.com". If provided, Traefik labels are added.
db_nameNoDatabase name to use (defaults to app_name)
app_nameNoName for the main application service (used as container name prefix)
stack_typeNoExplicit stack type. Use "auto" to detect from description.auto
descriptionNoNatural language description of what you want to build, e.g. "Node.js API with PostgreSQL and Redis cache"
node_versionNoNode.js version to use in image tags (default: "20")20
python_versionNoPython version to use in image tags (default: "3.12")3.12
traefik_networkNoExternal Docker network for Traefik (default: "proxy")proxy
Behavior3/5

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

With no annotations, the description bears full responsibility for behavioral disclosure. It mentions included security best practices and optional Traefik labels, but does not detail output format, error handling, or prerequisites. Adequate but not comprehensive.

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?

Two succinct sentences: first states the core purpose, second adds key feature (optional Traefik). No wasted words, front-loaded content.

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?

The description covers main functionality and key differentiators (security, Traefik). Given the high schema coverage and no output schema, it is sufficiently complete for a generation tool, though examples or output format clarification would improve it.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents parameters well. The description adds little beyond schema, only noting that domain triggers Traefik labels. Baseline 3 is appropriate.

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 clearly states that the tool generates a Docker Compose stack from a natural language description or a specific stack type. It lists included security features and optional Traefik labels. However, it does not explicitly differentiate from sibling tools like generate_dockerfile or add_traefik, which have overlapping scopes.

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?

The description implies usage when a full stack is needed but does not provide explicit guidance on when to use this tool versus alternatives (e.g., generate_dockerfile for a single Dockerfile). No when-not-to-use or exclusions are mentioned.

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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