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Algenta MCP Server

by io.github.thyn-ai
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list_deployment_regions

Read-onlyIdempotent

List available deployment providers and regions for the current organization. Read-only and non-destructive; not separately rate-limited. Call this before create_deployment to pick a valid provider/region pair. Returns the providers array with each provider's id, name, description, and regions (use a region id when creating).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_deployment_regions"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description reinforces this with 'Read-only and non-destructive.' It adds valuable context beyond the annotations: 'not separately rate-limited' and a concrete description of the return shape ('providers array with each provider's id, name, description, and regions').

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?

Three sentences with no filler. The core action and scope are front-loaded, followed by safety/rate-limit behavior, usage guidance, and return structure. Every sentence adds information the agent needs.

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?

The tool is simple (no parameters, no output schema), yet the description still covers what is returned, the structure of the return value, when to call it, and its safety profile. It is complete enough for an agent to invoke correctly without any further inference.

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?

The input schema has zero parameters and 100% coverage, so there is nothing for the description to explain about parameters. The description still adds useful output semantics by explaining what a region id should be used for, which is more than required for a no-parameter tool.

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?

States a specific action ('List available deployment providers and regions'), a clear scope ('for the current organization'), and directly ties the purpose to a sibling tool ('Call this before create_deployment'). This distinguishes it from other list-type tools in the sibling set, such as list_capability_providers.

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?

Explicitly states when to use the tool: 'Call this before create_deployment to pick a valid provider/region pair.' This names the dependent sibling and gives the agent a concrete precondition, leaving no ambiguity about when the tool is relevant.

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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