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ayoubzeroual

Perplexity MCP Server

by ayoubzeroual
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear and distinct purpose focused on web search with Perplexity AI.

    Naming Consistency5/5

    The single tool name 'perplexity_search_web' follows a consistent verb_noun pattern. Since there is only one tool, naming consistency is inherently perfect with no deviations to assess.

    Tool Count2/5

    A single tool is too few for a server named 'Perplexity MCP Server', which implies broader functionality. While the tool is well-defined, the server scope feels thin and limited, lacking additional operations like query refinement or result analysis that might be expected.

    Completeness2/5

    The server is severely incomplete for a web search domain. It only offers a basic search tool without any supporting operations such as filtering results, getting details, or managing search history, which are common in search interfaces and would be needed for agent workflows.

  • Average 2.8/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'recency filtering' but does not explain how this affects results, potential rate limits, authentication needs, error handling, or the nature of the search output (e.g., format, pagination). This leaves significant gaps in understanding the tool's behavior beyond basic functionality.

    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 a single, efficient sentence that front-loads the core functionality ('Search the web using Perplexity AI') and includes a key feature ('with recency filtering') without any wasted words. It is appropriately sized for the tool's complexity.

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

    Completeness2/5

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

    Given the complexity (a web search tool with filtering), no annotations, no output schema, and low schema description coverage, the description is incomplete. It lacks details on behavioral traits, parameter usage, result format, and error conditions, making it inadequate for the agent to fully understand how to invoke and interpret the tool effectively.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'recency filtering', which relates to the 'recency' parameter with enum values, adding some meaning. However, it does not explain the 'query' parameter or provide details on how recency filtering works (e.g., what 'day', 'week', etc., mean in practice), failing to fully compensate for the low coverage.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('Search the web') and the resource/context ('using Perplexity AI'), with the specific feature of 'recency filtering'. It provides a specific verb+resource combination that defines what the tool does. However, with no sibling tools mentioned, there's no opportunity to distinguish from alternatives, preventing a perfect score.

    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 mentions 'recency filtering' as a feature, which implies usage for time-sensitive searches, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., other search tools or methods). There are no stated exclusions, prerequisites, or comparisons, leaving the agent with minimal contextual direction.

    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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  • Evaluate tool definition quality.

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