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Rohit-Seelam

Perplexity MCP Server

by Rohit-Seelam
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Python

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    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

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