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by omnia-v
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

list dedicated templates

list_dedicated_templates
Read-onlyIdempotent

Retrieve the deployable model catalog and per-GPU-hour prices for dedicated endpoints, enabling valid deployment request construction and cost estimation.

Instructions

Returns the deployable model catalog for dedicated endpoints (model -> flavor -> GPU type -> allowed regions/counts/replica limits) plus this workspace's sell price per GPU-hour for every GPU/region combo — read it to build a valid POST /v1/dedicated request and estimate cost. GET /v1/dedicated/templates (API-key scope: read). Returns: { templates: [{ name (use as model_name), type ('text2text'|'embedding'|'image2text'|...), metadata?: { huggingface_url?, vendor?, context_window_k?, size_b?, license?: {url?, name?} }, flavors?: { <flavor_name>: { quantization?, use_cases?, tags?, base_model_slug?, available_configurations?: { gpu_configurations?: { <gpu_type>: { allowed_regions: string[], allowed_gpu_counts: int[], max_replicas_allowed: int } } } } } }], prices: [{ gpu_type, region, price_per_gpu_hour_usd: number|null }] }. Template contents are the upstream catalog shape, already snake_case. Notes: Scope via requiredScopeFor is 'read'; the local dedicated apiKeyActor does not enforce scopes. price_per_gpu_hour_usd is the customer price (base cost and margin are never returned); null means no price is configured for that combo yet and a deploy on it will be refused. 400 'Dedicated endpoints are not configured' or 'Failed to load dedicated endpoint catalog' on provider/config failure. Prices are quoted at request time; the price frozen on an endpoint is the one in effect when it is created. Free to call.

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_dedicated_templates"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations, it discloses auth behavior (the local dedicated apiKeyActor does not enforce scopes), pricing semantics (null means deployment will be refused; prices are quoted at request time and frozen at creation), and specific 400 error cases. This is substantial behavioral context that structured annotations cannot convey.

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 long but every section carries distinct value: purpose, route/scope, exact return shape, pricing/error caveats. It is front-loaded with the most decision-relevant information and stays organized despite the dense catalog schema.

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?

With no output schema or parameters, the description carries the full burden of explaining the response and the call's safety profile, and it does so exhaustively: templates schema, prices schema, error conditions, auth notes, and pricing freeze behavior. Nothing needed to invoke or interpret the call is missing.

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 tool takes zero parameters and the schema coverage is complete for that, so there are no parameter semantics for the description to add. The description instead documents the returned data structure, which is the relevant semantic information for this stateless read-only call.

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 identifies a specific resource ('deployable model catalog for dedicated endpoints') and explains its purpose: reading it lets you build a valid POST /v1/dedicated request and estimate cost. This clearly distinguishes it from siblings like list_dedicated_endpoints and create_dedicated_endpoint.

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?

It gives an explicit trigger context: use it before creating a dedicated endpoint to get valid model/flavor/GPU values and to estimate costs. It does not explicitly spell out when not to use it or name an alternative, but the intended usage is unmistakable.

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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