Skip to main content
Glama
aidenappl
by aidenappl

lattice_create_database_instance

Provision a database instance on a worker. Creates a real container with your chosen engine (MySQL, MariaDB, or PostgreSQL) and auto-allocates a free port.

Instructions

Provision a database instance on a worker. Creates a real container. Omit port to have a free one allocated automatically — that is the recommended path; a port already in use returns 409 naming the conflict

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesInstance name (must be unique)
portNoHost port to expose. Omit to auto-allocate a free port from the managed range (20000-29999)
engineYesDatabase engine
passwordNoApplication user's password
usernameNoApplication user to create
cpu_limitNoCPU limit in cores
worker_idYesWorker to provision on
memory_limitNoMemory limit in MEGABYTES (the API converts to bytes; values under 6MB are rejected by Docker)
database_nameNoInitial database to create
root_passwordNoRoot/superuser password
engine_versionNoEngine version tag; the API picks a default when omitted
retention_countNoHow many automatic snapshots to keep
snapshot_scheduleNoCron expression for automatic snapshots
adopt_existing_volumeNoReuse a leftover data volume of the same name. Off by default — the engine skips initialisation when its data directory is non-empty, so it keeps its OLD credentials while the API records the new ones, and nothing looks wrong until a connection fails
backup_destination_idNoBackup destination for snapshots
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It states that a real container is created and that using a port already in use yields a 409 conflict. However, it omits other important behaviors: success response, effects on existing resources, authentication needs, and whether the operation is idempotent. This is insufficient for a 15-parameter provisioning tool.

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 sentences, each serving a purpose. The first sentence states the primary action concisely. The second provides actionable guidance on a key parameter. There is no redundancy or filler. It is front-loaded with the core purpose.

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?

Given the complexity (15 parameters, no output schema), the description is brief. It explains the port behavior but does not describe the success return value, common error scenarios beyond 409, or how to interpret the result. For a tool with many optional parameters, the description is minimally adequate but could provide more context about defaults and outcomes.

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 description coverage is 100%, providing baseline meaning for all parameters. The description adds meaningful context beyond the schema: it explains the recommended usage for `port` (auto-allocation) and the error handling (409 on conflict). It also frames the overall action as creating a 'real container'. This adds value beyond the schema definitions.

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 the action ('Provision a database instance on a worker') and mentions it creates a real container. It is distinct from listing or updating database instances, but does not explicitly differentiate from the sibling tool `lattice_create_container` which also creates containers. Thus, it is clear but lacks explicit sibling differentiation.

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 provides specific guidance on the `port` parameter (recommendation to omit it and behavior on conflict: returns 409). However, it does not give broader usage context, such as when to use this tool versus alternatives like `lattice_create_container`, or prerequisites like requiring a worker. Some guidance is present but incomplete.

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/aidenappl/lattice-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server