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together-ai

Create a dedicated endpoint

together_create_endpoint
Destructive

Deploy a model on dedicated GPUs. The endpoint STARTS AUTOMATICALLY and bills per minute of uptime until stopped — set inactive_timeout to auto-stop it, and use together_list_hardware for valid hardware ids. Together: POST /endpoints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesThe model to deploy.
stateNoInitial state. Pass STOPPED to create without starting (and without billing).
hardwareYesHardware id, e.g. 1x_nvidia_a100_80gb_sxm.
autoscalingYesReplica bounds for autoscaling.
display_nameNoHuman-readable name.
inactive_timeoutNoMinutes of inactivity before auto-stop; 0 disables it.
availability_zoneNoAvailability zone, e.g. us-central-4b.
disable_speculative_decodingNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only carry destructiveHint=true, so the description must supply the operational picture — and it does, disclosing that the endpoint STARTS AUTOMATICALLY and bills per minute until stopped, and how to auto-stop it. It does not cover permissions, error modes, or provisioning latency, which keeps it short of a 5.

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 tight clauses with the cost warning front-loaded and the resource-routing hint last. Every sentence earns its place with no filler.

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?

For an 8-parameter, nested-schema creation tool with no output schema, the description covers the highest-risk facts (billing, auto-start, auto-stop, hardware-id lookup). It omits nothing critical, though listing the initial-state STOPPED trick inline would have made it self-contained against the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 88%, so the schema already documents most parameters. The description adds real meaning for inactive_timeout (auto-stop semantics) and hardware id sourcing, but leaves autoscaling, availability_zone, and disable_speculative_decoding entirely to the schema. Baseline with minor added value.

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 verb and resource ('Deploy a model on dedicated GPUs') and implicitly distinguishes creation from the sibling lifecycle tools together_start_endpoint and together_stop_endpoint. An agent can tell this creates a new endpoint rather than manipulating an existing one.

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?

Gives concrete routing guidance: 'use together_list_hardware for valid hardware ids' and 'set inactive_timeout to auto-stop it', plus the schema-level guidance to pass STOPPED to avoid billing. It does not explicitly contrast this with together_start_endpoint, but the create-vs-start distinction is clear from context.

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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