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MCP Perplexity Pro

by cfdude

Perplexity Models

perplexity_models
Read-only

List available Perplexity models for your configured key with live prices, and view documented Agent API presets, optionally filtered by provider or refreshed.

Instructions

List the models available to the configured key with their prices (live data), plus the documented Agent API presets as a separate section.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refreshNoBypass the cache and fetch the list now
providerNoOnly models from this provider (case-insensitive), e.g. anthropic

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
staleYesTrue when the live request failed and a cached list is shown
modelsYesLive models (after the provider filter)
presetsYesDocumented Agent API presets; not live data
routingYesActive routing; configuration, not live data
providersYesEvery provider in the live list, ignoring the filter
age_secondsYesSeconds since the list was fetched live

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds useful behavioral context beyond them: the data is live and priced, and the response contains a distinct Agent API presets section, which tells the agent what to expect from a remote fetch.

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?

A single, front-loaded sentence with the primary resource first and the secondary output section appended. No filler or redundancy.

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?

With an output schema present, the description need not explain return values, yet it still flags the two-section output. Annotations cover safety; the only unaddressed item is when to prefer a fresh fetch over the cache.

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%, so both parameters (refresh, provider) are fully documented in the schema. The description adds no syntax or format detail beyond that, which is the expected baseline when the schema does the heavy lifting.

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 names a specific verb (list) and resource (models) and even scopes it to the configured key with prices. It is trivially distinguishable from every sibling (ask, chat, search, embed, usage), none of which enumerate models.

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?

Usage is implied: an agent should call this to discover available models and their prices. However, there is no explicit when-to-use instruction and no mention of alternatives (e.g., perplexity_help for documentation) or when the cache should be refreshed.

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