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MIt9

perplexity-pro-mcp

by MIt9

perplexity_search

Search the web with advanced AI, receiving detailed answers that include citations. Adjust mode for thorough or quick results and focus on academic, writing, or video content.

Instructions

Search the web using Perplexity AI Pro. Returns a detailed answer with citations and sources.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNocopilot = deep multi-step search, concise = quick answercopilot
focusNoSearch focusinternet
modelNoModel to usepplx_pro
queryYesSearch query
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only states 'returns a detailed answer with citations and sources,' omitting critical traits such as authentication needs, rate limits, cost implications, or what happens in error cases. This leaves significant gaps for an agent.

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 two sentences, front-loaded with the core action, and contains no extraneous information. Every word earns its place, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description should provide more behavioral and return-value context. It briefly mentions 'detailed answer with citations and sources' but lacks structure details, error handling, or usage boundaries. The rich schema helps, but completeness remains average.

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 each parameter having a description and enums clearly labeled. The top-level description adds no additional parameter context beyond the schema, meeting the baseline for full coverage but not surpassing it.

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 clearly states the tool's purpose: 'Search the web using Perplexity AI Pro. Returns a detailed answer with citations and sources.' It specifies the verb (search), resource (web using Perplexity), and distinguishes it from sibling tools that deal with collections, export, follow-up, or threads.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like follow-up or threads. It does not mention prerequisites, limitations, or preferred contexts. The schema's enum hints at usage (copilot vs concise) but the description itself lacks explicit usage guidelines.

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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