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Glama
Rohit-Seelam

Perplexity MCP Server

by Rohit-Seelam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
PERPLEXITY_API_KEYYesYour Perplexity API key from settings page (https://www.perplexity.ai/settings/api)

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
perplexity_smallA
Quick and reliable queries using Perplexity's sonar-pro model.

Best for: Fast factual questions, basic research, immediate answers.
Uses default parameters for optimal speed and cost-effectiveness.

Args:
    query: The question or prompt to send to Perplexity
    messages: Optional conversation context (list of {"role": "user/assistant", "content": "..."})

Returns:
    Dictionary with content and citations
perplexity_mediumA
Enhanced reasoning with moderate search depth using sonar-reasoning-pro.

Best for: Complex questions requiring analysis, moderate research depth, 
technical explanations with citations.
Uses medium reasoning effort and search context size.

Args:
    query: The question or prompt to send to Perplexity
    messages: Optional conversation context (list of {"role": "user/assistant", "content": "..."})

Returns:
    Dictionary with content and citations
perplexity_largeA
Comprehensive research with maximum depth using sonar-deep-research.

Best for: Deep research tasks, comprehensive analysis, complex multi-step reasoning,
academic research, detailed technical investigations.
Uses high reasoning effort and search context size.

WARNING: This tool may take significantly longer (potentially 10-30 minutes) 
and may timeout on very complex queries.

Args:
    query: The question or prompt to send to Perplexity
    messages: Optional conversation context (list of {"role": "user/assistant", "content": "..."})

Returns:
    Dictionary with content and citations

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.5/5.0

Scored across 3 tools

Disambiguation5/5

The three tools are clearly distinguished by their intended use cases and performance characteristics: 'large' for deep research with maximum depth, 'medium' for enhanced reasoning with moderate depth, and 'small' for quick factual queries. Each tool's description explicitly outlines its best applications, reasoning effort, and expected response times, leaving no ambiguity about when to select which tool.

Naming Consistency5/5

All tool names follow a perfectly consistent pattern: 'perplexity_' prefix followed by a size descriptor ('large', 'medium', 'small'). This naming convention immediately communicates that these are variations of the same core functionality with different scales, making the tool set predictable and easy to understand.

Tool Count5/5

Three tools is an ideal number for this server's purpose: providing access to Perplexity's AI models at different capability levels. Each tool serves a distinct role in the research/query workflow, from quick lookups to comprehensive analysis, and no tool feels redundant or missing for the domain.

Completeness5/5

The tool set provides complete coverage for the server's domain of Perplexity AI queries. It offers a full spectrum of query capabilities from simple to complex, with clear guidance on when to use each tool. The consistent argument structure (query + optional messages) and return format ensure agents can work seamlessly across all tools without encountering dead ends or missing functionality.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources