A
licenseB
qualityF
maintenanceA server facilitating web search functionality by utilizing Perplexity AI's API, designed to integrate with the Claude desktop client for enhanced search queries.
1
308
MIT
Perplexity MCP Server
by jaacob
Perplexity MCP サーバー
Perplexity の API を使用して Web 検索機能を提供する MCP サーバー。
前提条件
Node.js (v14以上)
Perplexity API キー ( https://www.perplexity.ai/settings/apiで取得)
クロードデスクトップアプリ
Related MCP server: Perplexity Web Search MCP Server
インストール
Smithery経由でインストール
Smithery経由で Claude Desktop 用の Perplexity Server を自動的にインストールするには:
npx -y @smithery/cli install @jaacob/perplexity-mcp --client claude手動インストール
このリポジトリをクローンします:
git clone https://github.com/jaacob/perplexity-mcp cd perplexity-mcp依存関係をインストールします:
npm installサーバーを構築します。
npm run build
構成
https://www.perplexity.ai/settings/apiから Perplexity API キーを取得します。
~/Library/Application Support/Claude/claude_desktop_config.jsonにある Claude の設定ファイルにサーバーを追加します。
{
"mcpServers": {
"perplexity-server": {
"command": "node",
"args": [
"/absolute/path/to/perplexity-mcp/build/index.js"
],
"env": {
"PERPLEXITY_API_KEY": "your-api-key-here",
"PERPLEXITY_MODEL": "sonar"
}
}
}
}/absolute/path/toリポジトリのクローンを作成した実際のパスに置き換えます。
利用可能なモデル
PERPLEXITY_MODEL環境変数を設定することで、使用するモデルを指定できます。使用可能なオプションは次のとおりです。
sonar-reasoning-pro- 強化された推論機能を備えた最も有能なモデルsonar-reasoning- 強化された推論機能sonar-pro- 応答時間の高速化sonar- デフォルトモデル（モデルが指定されていない場合に使用）
最新のモデルの価格と在庫状況については、 https://docs.perplexity.ai/guides/pricingをご覧ください。
使用法
サーバーを設定してClaudeを再起動すれば、Claudeに情報を検索するよう指示するだけで済みます。例えば：
「SpaceXの最新ニュースは何ですか？」
「シカゴの最高のレストランを検索」
「ジャズ音楽の歴史に関する情報を見つける」
Claude は、Perplexity 検索ツールを自動的に使用して、関連する情報を検索して返します。
何らかの理由で実行されない場合は、プロンプトの前に「Web を検索」を追加して強制的に実行することができます。
発達
サーバーを変更するには:
src/index.tsを編集するnpm run buildでリビルドする変更をロードするにはClaudeを再起動してください
ライセンス
マサチューセッツ工科大学
Available Tools
1 toolsearchC
Search the web using Perplexity AI
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | The search query |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Search the web' implies a read-only operation, it doesn't specify rate limits, authentication requirements, result format, pagination, or any other behavioral characteristics. The description is minimal and lacks important operational context.
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 - a single sentence that directly states the tool's function. There's zero waste or unnecessary verbiage. It's appropriately sized for a simple search tool and front-loaded with the essential information.
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?
For a search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of results to expect, whether there are limitations on query types, how results are formatted, or any other operational details. The description leaves too many questions unanswered for effective tool usage.
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 clearly documented. The description doesn't add any additional parameter semantics beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no parameter information in the description.
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 specifies the resource/context ('using Perplexity AI'), making the purpose immediately understandable. It's not a tautology and provides specific information about what the tool does. However, since there are no sibling tools mentioned, it cannot demonstrate differentiation from alternatives.
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 no guidance on when to use this tool versus alternatives, prerequisites, or specific contexts where it's most appropriate. It simply states what the tool does without any usage context or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
search
TDQS
B3.1/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap between tools, making disambiguation perfect. The tool's purpose is clearly defined as web search using Perplexity AI, leaving no room for misselection.
Naming Consistency5/5
A single tool named 'search' follows a consistent and straightforward verb-based naming pattern. There are no other tools to compare against, so no inconsistency can exist in the naming scheme.
Tool Count2/5
One tool is too few for a server named 'Perplexity MCP Server', which implies broader capabilities beyond just search. A single tool feels thin and under-scoped for what might be expected from a Perplexity AI integration, such as additional operations like summarization or follow-up queries.
Completeness2/5
The tool surface is severely incomplete for a web search domain; it only offers a basic search function without any complementary tools for refining results, getting summaries, or handling related queries. This creates significant gaps that could lead to agent failures in complex tasks.
Maintenance
ActivityInactive
ResponsivenessNo issues
Related MCP Connectors
Real-time web search, reasoning, and research through Perplexity's API
Enable AI assistants to perform web searches using Perplexity's Sonar Pro.
Provides AI assistants with access to Seltz's powerful Web Search capabilities.
Web search, agentic search, news, page retrieval, sitemaps, and trending topics through Search1API.
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