MCP 服务器

Perplexity MCP Server

Integrates with Perplexity's API to provide web search and AI-powered answers with citations. Offers a three-tier research workflow: search for sources, ask for grounded AI answers, and ask_more for deeper analysis using advanced models.

README

Perplexity MCP Server

A FastMCP server that integrates with Perplexity's API to provide web search and grounded AI answers.

Features

Three-Tier Research Workflow

search - Ground yourself first
- Find relevant sources before asking questions
- Returns URLs, titles, and snippets
- Use this when you don't know about a topic
ask - Get AI answers (DEFAULT)
- AI-synthesized answers with web grounding
- Uses the sonar model (fast and cost-effective)
- Includes citations and optional images/related questions
ask_more - Dig deeper
- More comprehensive analysis for complex questions
- Uses the sonar-pro model (more capable but pricier)
- Use when ask doesn't provide sufficient depth

Prerequisites

Python 3.10 or higher
A Perplexity API key
uv (recommended) or pip

Local Setup

1. Install Dependencies

Using uv (recommended):

uv pip install -e .

Or using pip:

pip install -e .

2. Configure API Key

Copy the example environment file:

cp .env.example .env

Edit .env and add your Perplexity API key:

PERPLEXITY_API_KEY=your_api_key_here

3. Run the Server

Test the server locally:

uv run fastmcp run server.py

Or with the fastmcp CLI:

fastmcp run server.py

4. Install in Claude Desktop

Install the server for use with Claude Desktop:

fastmcp install claude-code server.py

Or manually add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "perplexity": {
      "command": "uv",
      "args": ["run", "fastmcp", "run", "/absolute/path/to/server.py"],
      "env": {
        "PERPLEXITY_API_KEY": "your_api_key_here"
      }
    }
  }
}

Cloud Deployment (FastMCP Cloud)

Deploy to fastmcp.cloud for easy hosting:

1. Push to GitHub

git init
git add .
git commit -m "Initial commit"
git remote add origin https://github.com/yourusername/perplexity-mcp.git
git push -u origin main

2. Deploy on FastMCP Cloud

Visit fastmcp.cloud
Sign in with GitHub
Create a new project and connect your repo
Configure:
- Entrypoint: server.py
- Environment Variables: Add PERPLEXITY_API_KEY
Deploy!

Your server will be available at https://your-project-name.fastmcp.app/mcp

FastMCP Cloud automatically:

✅ Detects dependencies from pyproject.toml
✅ Deploys on every push to main
✅ Creates preview deployments for PRs
✅ Handles HTTP transport and authentication

Tool Usage Guide

Research Workflow Example

1. Don't know about a topic? → Use search()
   search("latest AI research papers on transformers")

2. Found sources? → Use ask() to understand
   ask("What are the key innovations in transformer models?")

3. Need more depth? → Use ask_more()
   ask_more("Explain the mathematical foundations of attention mechanisms in transformers")

Tool Parameters

`search(query, max_results=10, recency=None, domain_filter=None)`

query: Search query string
max_results: Number of results (default: 10)
recency: Filter by time - "day", "week", "month", or "year"
domain_filter: Include/exclude domains
- Include: ["wikipedia.org", "github.com"]
- Exclude: ["-reddit.com", "-pinterest.com"]

`ask(query, reasoning_effort="medium", ...)`

query: Question to ask
reasoning_effort: "low", "medium" (default), or "high"
search_mode: "web" (default), "academic", or "sec"
recency: Time filter
domain_filter: Domain filter
return_images: Include images (default: False)
return_related_questions: Include follow-up questions (default: False)

`ask_more(query, reasoning_effort="medium", ...)`

Same parameters as ask(), but uses the more powerful sonar-pro model.

Cost Optimization

Start with search: Free/cheap way to find sources
Default to ask: Uses sonar (cost-effective)
Escalate to ask_more: Only when needed (more expensive)

Development

Project Structure

perplexity-mcp/
├── server.py           # Main FastMCP server
├── pyproject.toml      # Dependencies
├── .env.example        # Environment template
└── README.md          # This file