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config_create

Create an immutable Docker Swarm config object to store non-sensitive configuration files like nginx.conf or app.yaml for mounting into service containers.

Instructions

Create an immutable Swarm config object; requires a swarm manager.

Configs store non-sensitive configuration files (nginx.conf, app.yaml, etc.) and mount them into service containers at a specified path. Unlike secrets, config data is not encrypted at rest - use secret_create for credentials or keys. data is raw bytes; encode strings first (e.g. "my config".encode()). Once created, a config is immutable: to update it, create a new config with a new name and update the service to reference it, then remove the old config with config_remove.

Args: name: Unique config name within the swarm data: Raw bytes content of the config file labels: Labels to set on the config templating: Templating driver config (e.g. {"Name": "golang"} for Go template syntax)

Returns: dict: The created config's full document ({"ID", "Version", "CreatedAt", "Spec", ...})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
nameYes
labelsNo
templatingNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.0

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that configs are immutable, not encrypted at rest, require a swarm manager, and that data must be raw bytes with encoding guidance for strings. This gives an agent clear expectations about the tool's behavior and constraints.

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 compact and well-structured, front-loading the core purpose before param details and return information. Every sentence adds value, with an example for templating and clear guidance for data encoding.

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 there is no output schema, the description explicitly documents the return value shape. It also covers usage constraints, alternatives, immutability implications, and all four parameters, leaving little an agent would need to infer.

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%, yet the description explains every parameter meaningfully: name uniqueness, raw byte content, label assignment, and templating driver config with a concrete example. It compensates fully for the schema's lack of descriptions.

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 it creates an immutable Swarm config object with a specific verb and resource. It distinguishes itself from secret_create by noting configs are not encrypted at rest, and hints at its role of mounting files into service containers.

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 guidance: use secret_create for credentials or keys, and explains the update workflow by creating a new config and removing the old one with config_remove. It also states the prerequisite that a swarm manager is required.

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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