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quequiere

perplexity-web-mcp

by quequiere

search_advanced

Search Perplexity.ai with specific source selection to combine web, academic, and social sources for queries where source control matters.

Instructions

Search Perplexity.ai with specific source selection. Lets you combine multiple sources (e.g. web + academic). Use this when source control matters; prefer search for general queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query
sourcesYesSources to search: 'web' (general web), 'academic' (scholarly articles), 'social' (Reddit & forums). Can combine multiple.

Implementation Reference

  • Tool execution handler for search_advanced, which invokes searchWithSources.
    execute: async ({ query, sources }) => {
      await ensureBrowser();
      const result = await searchWithSources(query, TIMEOUT_MS, sources);
      return formatResult(result);
    },
  • Handler implementation for searching with specific sources, which calls runSearch.
    export async function searchWithSources(query: string, timeoutMs: number, sources: string[]): Promise<SearchResult> {
      log(`Search: "${query}" sources=[${sources.join(",")}] (timeout: ${timeoutMs}ms)`);
      return runSearch(query, timeoutMs, sources);
    }
  • src/index.ts:42-58 (registration)
    Registration of the search_advanced MCP tool.
    mcp.addTool({
      name: "search_advanced",
      description:
        "Search Perplexity.ai with specific source selection. Lets you combine multiple sources (e.g. web + academic). Use this when source control matters; prefer `search` for general queries.",
      parameters: z.object({
        query: z.string().describe("The search query"),
        sources: z
          .array(z.enum(["web", "academic", "social"]))
          .min(1)
          .describe("Sources to search: 'web' (general web), 'academic' (scholarly articles), 'social' (Reddit & forums). Can combine multiple."),
      }),
      execute: async ({ query, sources }) => {
        await ensureBrowser();
        const result = await searchWithSources(query, TIMEOUT_MS, sources);
        return formatResult(result);
      },
    });
Behavior3/5

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 performs a search operation but doesn't describe behavioral aspects like rate limits, authentication requirements, response format, pagination, or error conditions. While it hints at the tool's scope ('specific source selection'), it lacks details about what the search returns or how it behaves operationally.

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 extremely concise and well-structured in just two sentences. The first sentence states the core purpose, the second provides usage guidance with a clear alternative. Every word earns its place with no redundancy or fluff, making it easy to parse and understand quickly.

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 the tool has 2 parameters with 100% schema coverage but no annotations and no output schema, the description is moderately complete. It covers purpose and usage guidelines well but lacks behavioral details (e.g., what the search returns, performance characteristics) that would be helpful for an agent. For a search tool with no output schema, more information about result format would improve completeness.

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%, so the schema already fully documents both parameters. The description adds minimal value beyond the schema: it mentions 'combine multiple sources' which aligns with the schema's array type for 'sources', and gives an example ('e.g. web + academic'), but doesn't provide additional semantic context like parameter interactions or usage nuances. This meets the baseline for high schema coverage.

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 Perplexity.ai with specific source selection. Lets you combine multiple sources (e.g. web + academic).' It specifies the verb ('Search'), resource ('Perplexity.ai'), and unique capability ('specific source selection' with ability to combine sources), effectively distinguishing it from the sibling 'search' tool.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool versus alternatives: 'Use this when source control matters; prefer `search` for general queries.' It clearly names the alternative tool ('search') and specifies the condition for choosing this tool ('when source control matters'), offering complete usage guidance.

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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