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quequiere

perplexity-web-mcp

by quequiere

search

Search the web to get AI-synthesized answers with cited sources for your queries. Provides comprehensive information from multiple sources in one response.

Instructions

Search the web using Perplexity.ai and get an AI-synthesized answer with cited sources. Uses default Perplexity settings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query

Implementation Reference

  • src/index.ts:28-40 (registration)
    Tool registration for "search" in src/index.ts using FastMCP.
    mcp.addTool({
      name: "search",
      description:
        "Search the web using Perplexity.ai and get an AI-synthesized answer with cited sources. Uses default Perplexity settings.",
      parameters: z.object({
        query: z.string().describe("The search query"),
      }),
      execute: async ({ query }) => {
        await ensureBrowser();
        const result = await search(query, TIMEOUT_MS);
        return formatResult(result);
      },
    });
  • The handler function for the "search" tool logic.
    export async function search(query: string, timeoutMs: number): Promise<SearchResult> {
      log(`Search: "${query}" (timeout: ${timeoutMs}ms)`);
      return runSearch(query, timeoutMs, null);
    }
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 the tool uses Perplexity.ai and provides AI-synthesized answers with citations, but lacks details on rate limits, authentication needs, error handling, or response format. For a search tool with no annotations, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, consisting of two sentences that efficiently convey the core functionality and a key behavioral note. There's no wasted text, though it could be slightly more structured (e.g., separating purpose from settings).

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 no annotations and no output schema, the description is incomplete for a search tool. It doesn't explain the response format (e.g., structure of AI-synthesized answers, citation details), error cases, or dependencies like authentication (implied by 'login' sibling). For a tool with external API integration, this lacks sufficient context.

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 input schema has 100% description coverage, with the 'query' parameter documented as 'The search query.' The description doesn't add any parameter-specific details beyond what the schema provides, such as query formatting or examples. With high schema coverage, the baseline score of 3 is appropriate.

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 tool's purpose: 'Search the web using Perplexity.ai and get an AI-synthesized answer with cited sources.' It specifies the action (search), resource (web via Perplexity.ai), and output type (AI-synthesized answer with citations). However, it doesn't explicitly differentiate from sibling tools like 'search_advanced' beyond mentioning 'default Perplexity settings.'

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 minimal usage guidance. It mentions 'Uses default Perplexity settings,' which implies this is a basic search tool, but doesn't explicitly state when to use this vs. 'search_advanced' or 'login.' No context on alternatives, prerequisites, or exclusions is provided.

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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