About perplexity-mcp MCP server
perplexity-mcp is an MCP server that gives clients web search through Perplexity AI's API. It is aimed at users who want search inside Claude Desktop or Cursor.
Key features
- 01Exposes a perplexity_search_web tool
- 02Filters results by day, week, month or year
- 03Selects the Perplexity model via environment variable
- 04Launches with uvx
Use cases
- 01Finding recent news about a company from the past week
- 02Searching the web from Cursor during coding
- 03Running time-bounded web searches in Claude Desktop
MCP support
This is an MCP server that exposes a perplexity_search_web tool and a matching prompt to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEperplexity-mcp MCP server
A Model Context Protocol (MCP) server that provides web search functionality using Perplexity AI's API. Works with the Anthropic Claude desktop client.
Example
Let's you use prompts like, "Search the web to find out what's new at Anthropic in the past week."
Glama Scores
Components
Prompts
The server provides a single prompt:
- perplexity_search_web: Search the web using Perplexity AI
- Required "query" argument for the search query
- Optional "recency" argument to filter results by time period:
- 'day': last 24 hours
- 'week': last 7 days
- 'month': last 30 days (default)
- 'year': last 365 days
- Uses Perplexity's API to perform web searches
Tools
The server implements one tool:
- perplexity_search_web: Search the web using Perplexity AI
- Takes "query" as a required string argument
- Optional "recency" parameter to filter results (day/week/month/year)
- Returns search results from Perplexity's API
Installation
Installing via Smithery
To install Perplexity MCP for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install perplexity-mcp --client claude
Requires UV (Fast Python package and project manager)
If uv isn't installed.
# Using Homebrew on macOS
brew install uv
or
# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows.
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Environment Variables
The following environment variable is required in your claude_desktop_config.json. You can obtain an API key from Perplexity
PERPLEXITY_API_KEY: Your Perplexity AI API key
Optional environment variables:
-
PERPLEXITY_MODEL: The Perplexity model to use (defaults to "sonar" if not specified)Available models:
sonar-deep-research: 128k context - Enhanced research capabilitiessonar-reasoning-pro: 128k context - Advanced reasoning with professional focussonar-reasoning: 128k context - Enhanced reasoning capabilitiessonar-pro: 200k context - Professional grade modelsonar: 128k context - Default modelr1-1776: 128k context - Alternative architecture
And updated list of models is avaiable (here)[https://docs.perplexity.ai/guides/model-cards]
Cursor & Claude Desktop Installation
Add this tool as a mcp server by editing the Cursor/Claude config file.
"perplexity-mcp": {
"env": {
"PERPLEXITY_API_KEY": "XXXXXXXXXXXXXXXXXXXX",
"PERPLEXITY_MODEL": "sonar"
},
"command": "uvx",
"args": [
"perplexity-mcp"
]
}
Cursor
- On MacOS:
/Users/your-username/.cursor/mcp.json - On Windows:
C:\Users\your-username\.cursor\mcp.json
If everything is working correctly, you should now be able to call the tool from Cursor.
Claude Desktop
- On MacOS:
~/Library/Application\ Support/Claude/claude_desktop_config.json - On Windows:
%APPDATA%/Claude/claude_desktop_config.json
To verify the server is working. Open the Claude client and use a prompt like "search the web for news about openai in the past week". You should see an alert box open to confirm tool usage. Click "Allow for this chat".
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.