Perplexity MCP Server
@RossH121
关于 Perplexity MCP Server
A Perplexity MCP server based on https://github.com/jaacob/perplexity-mcp which includes additional tools supporting domain filtering, search recency and model routing
基本信息
配置
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概览
What is Perplexity MCP Server?
An MCP server that provides Perplexity AI web search capabilities to Claude, with automatic model selection, stateful filters, and 10 purpose-built tools. It is designed for users of Claude Desktop or any MCP-compatible client who need AI-powered search, deep research, raw web results, agentic loops, and embeddings.
How to use Perplexity MCP Server?
Install Node.js v20 or higher, obtain a Perplexity API key, and ensure you have Claude Desktop (or any MCP-compatible client). Clone the repository, run npm install and npm run build. Add the server to Claude’s config file (claude_desktop_config.json) with the command, absolute path to the built index.js, and environment variables PERPLEXITY_API_KEY and PERPLEXITY_MODEL. After restarting Claude, you can invoke the search, raw_search, async_research, agent, embeddings, and filter tools.
Key features of Perplexity MCP Server
- 10 purpose-built tools covering search, raw results, research, agent, and embeddings
- Automatic model selection based on query keywords (sonar, sonar-pro, sonar-reasoning-pro, sonar-deep-research)
- Stateful domain allowlist/blocklist and recency time-window filters
- Asynchronous deep research jobs that can be polled, surviving 7 days
- Agentic loop with built-in tools (web_search, fetch_url) and optional third-party models
- Embeddings generation via pplx-embed models with Matryoshka dimensions
Use cases of Perplexity MCP Server
- Time-sensitive research with domain filtering: set recency to week, allow only specific domains, then search for recent breakthroughs
- Financial document research: use raw_search with SEC mode to find filings, then search for synthesized analysis
- Academic literature review: search with academic mode and high context size for peer-reviewed sources
- Deep research with reasoning control: run search with high reasoning effort and strip thinking blocks for clean output
- Quick fact-checking: use raw_search to get ranked results without AI synthesis, cheaper and faster
FAQ from Perplexity MCP Server
What are the prerequisites for Perplexity MCP Server?
Node.js v20 or higher, a Perplexity API key (get one at https://www.perplexity.ai/settings/api), and Claude Desktop or any MCP-compatible client.
How does automatic model selection work?
The server scores your query against keyword lists. Research keywords (e.g., "deep research", "comprehensive") trigger sonar-deep-research; reasoning keywords (e.g., "solve", "logic") trigger sonar-reasoning-pro; simple keywords (e.g., "quick", "brief") trigger sonar; everything else uses sonar-pro. A strong match (score ≥ 2) overrides a manually set model.
What models are available and how can I set a default?
Available models: sonar-deep-research, sonar-reasoning-pro, sonar-pro, sonar. Set a default via the PERPLEXITY_MODEL environment variable, or use the model_info tool to view and override the current selection.
Can I use streaming responses?
Yes, the search tool accepts a stream boolean parameter and a stream_mode parameter (full or concise) for Pro Search streaming events.
How do filters work and are they persistent?
Domain filters (allowlist/blocklist) and recency filters persist across all subsequent searches until cleared. Use clear_filters to reset all, list_filters to view active filters. Maximum 20 domains; cannot mix allow and block in the same filter set.
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