Skip to main content
Glama

List render nodes

list_nodes
Read-onlyIdempotent

The EvaFarm node catalog with live status (available / busy / reserved / maintenance / ai — busy with an AI workload until status_until, not for rent), hardware, hourly price and installed software and render engines. Filter to find a machine for a job.

Input Schema

NameRequiredDescriptionDefault
gpuNoGPU model substring, e.g. "4090" or "5090".
engineNoRequired render engine, e.g. "redshift", "octane", "cycles".
currencyNoPrice currency. Default RUB.
softwareNoRequired application, e.g. "cinema4d", "blender", "houdini".
available_onlyNoOnly nodes free to rent right now.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuine domain semantics annotations cannot express: the meaning of each status value, including the non-obvious 'ai' state (busy with an AI workload until status_until, not for rent), which prevents mis-selecting an unavailable node.

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?

Two tight sentences, with the catalog payload and its status vocabulary front-loaded before the filtering hint. Slightly run-on in the status parenthetical, but nothing is wasted.

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?

No output schema exists, so the description must convey the return shape — it does so by naming the per-node fields (status, hardware, price, software, engines). It stops short of describing ordering, pagination or result volume, which a catalog tool could reasonably address.

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 description coverage is 100% with examples for gpu, engine, software, currency and available_only, so the baseline is 3. The description adds only the general framing that these filters target 'a job', not any per-parameter syntax or interaction detail beyond the schema.

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?

States a specific verb+resource ('The EvaFarm node catalog') and enumerates what the listing carries: live status, hardware, hourly price, software and render engines. It does not explicitly contrast itself with sibling list-adjacent tools like get_node or estimate_cost, so it lands at 4 rather than 5.

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?

'Filter to find a machine for a job' implies the browse-and-filter use case, but there is no statement of when to prefer this over get_node (single node) or estimate_cost (pricing a job). Usage is implied rather than directed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources