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khronos224

Perplexity API Platform MCP Server

by khronos224

Ask Perplexity

perplexity_ask
Read-only

Answer quick factual questions with web-grounded AI and numbered citations. Filter results by recency, domain, or search context for concise summaries and explanations.

Instructions

Answer a question using web-grounded AI (Perplexity Agent API, fast preset). Best for: quick factual questions, summaries, explanations, and general Q&A. Returns a text response with numbered citations. Fastest and cheapest option. Supports filtering by recency (hour/day/week/month/year), domain restrictions, and search context size. For in-depth multi-source research, use perplexity_research instead. For step-by-step reasoning and analysis, use perplexity_reason instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messagesYesArray of conversation messages
search_context_sizeNoControls how much web context is retrieved. 'low' is fastest, 'high' provides more comprehensive results.
search_domain_filterNoRestrict search results to specific domains (e.g., ['wikipedia.org', 'arxiv.org']). Use '-' prefix for exclusion (e.g., ['-reddit.com']).
search_recency_filterNoFilter search results by recency. Use 'hour' for very recent news, 'day' for today's updates, 'week' for this week, etc.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
responseYesAI-generated text response with numbered citation references

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds meaningful behavior beyond that: it is web-grounded, uses the fast preset, returns text with numbered citations, and is the fastest/cheapest option. It doesn't cover rate limits or failure behavior, but the annotation bar is lower and the added details are substantive.

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 front-loaded with the core purpose and then efficiently packs in use cases, return format, performance characteristics, filtering capabilities, and routing guidance to sibling tools. Every sentence earns its place; there is no filler or redundancy.

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?

For a read-only Q&A tool, the description covers purpose, use cases, return shape, filtering options, and explicit alternatives. The input schema fully documents all parameters, annotations cover safety, and an output schema exists, so the description is sufficiently complete for an agent to select and invoke it correctly.

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?

The schema covers 100% of parameter descriptions, so the baseline is 3. The description references recency filtering, domain restrictions, and search context size, but it does not add detail beyond what the schema already explains. It adds no new semantic meaning for the parameters.

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 uses a specific verb ('Answer') and resource ('web-grounded AI / Perplexity Agent API') and clearly positions the tool for quick factual questions, summaries, and general Q&A. It explicitly distinguishes this tool from perplexity_research and perplexity_reason by naming those alternatives and their different purposes.

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?

It states exactly when to use this tool ('quick factual questions, summaries, explanations, and general Q&A') and when to use alternatives instead ('in-depth multi-source research' → perplexity_research; 'step-by-step reasoning and analysis' → perplexity_reason). This gives an agent clear routing criteria.

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

Install Server

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