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Anythink-MCP

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projects_create

Create an isolated Anythink backend instance with database, API, auth, and storage. Asynchronous provisioning returns project ID and API URL.

Instructions

Provision a new project — a dedicated, isolated Anythink backend instance with its own database, API, auth, and storage. Requires platform login and an active billing account (set one with 'accounts_use'). Provisioning runs asynchronously: the project starts in a Provisioning state, so poll 'projects_list' until it is Active. Returns the new project's id, name, org id, and API URL. Connect to it with 'projects_use'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesHuman-readable project name, e.g. 'production' or 'my-app'
planIdYesPlan id (UUID) that sets the project's resource tier and pricing. Run the 'plans' CLI command (via the 'cli' tool) to list available plan ids.
regionNoDeployment region slug, e.g. 'lon1'. Defaults to 'lon1'. Choose the region closest to your users.lon1
accountIdNoBilling account id to create the project in. Defaults to the active account set via 'accounts_use'.
descriptionNoOptional free-text description shown in the dashboard
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses asynchronous provisioning, required billing account, and return fields (id, name, org id, API URL). It does not contradict any annotations (none present) and adequately covers behavioral traits for a creation tool.

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?

The description is a single paragraph that is well-structured: main action, prerequisites, behavior, output. Every sentence adds useful information. It is appropriately sized for a creation tool with moderate complexity.

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?

Given no output schema and no annotations, the description covers purpose, prerequisites, async behavior, and return fields. It addresses how to monitor progress and connect. It could mention error handling or billing failure scenarios, but overall it is fairly complete.

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%, and the description adds meaningful context beyond the schema: e.g., name is 'human-readable', planId references the 'plans' CLI command, region defaults to 'lon1', accountId defaults to active account, description as optional. This adds value without redundancy.

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 uses a specific verb ('Provision') and identifies the resource ('new project') with a clear definition as 'a dedicated, isolated Anythink backend instance'. It distinguishes from sibling tools like projects_list, projects_use, and projects_delete.

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?

The description states prerequisites ('Requires platform login and an active billing account') and provides context on asynchronous behavior with polling instructions, along with a reference to connect using 'projects_use'. It mentions alternatives implicitly (accounts_use, projects_list) but does not explicitly state when not to use this tool.

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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