Perplexity Search
Access the Perplexity search API for real-time information and answers.
Perplexity Search MCP Server
A Go implementation of a Perplexity Search MCP server that allows large language models (LLMs) to access the Perplexity search API through the Model Context Protocol (MCP).
Features
- perplexity_search: Perform web searches and return results, including citations
- Parameters:
query(string, required): The search querysearch_recency_filter(string, optional): Filter results by time (month,week,day,hour)max_tokens(integer, optional): Maximum number of tokens to returntemperature(number, optional, default: 0.2): Controls randomness in responsetop_p(number, optional, default: 0.9): Nucleus sampling thresholdsearch_domain_filter(array, optional): List of domains to limit search resultsreturn_images(boolean, optional): Include image links in resultsreturn_related_questions(boolean, optional): Include related questionstop_k(number, optional, default: 0): Number of tokens for top-k filteringstream(boolean, optional): Stream response incrementallypresence_penalty(number, optional, default: 0): Adjust likelihood of new topicsfrequency_penalty(number, optional, default: 1): Reduce repetitionweb_search_options(object, optional): Configuration options for web search
- Parameters:
Setup & Usage
Installing via Smithery
To install Perplexity Search Golang for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @chenxilol/perplexity-mcp-go --client claude
Prerequisites
- Go 1.23 or higher
- Perplexity API key
Installation
- Clone the repository:
git clone https://github.com/chenxilol/perplexity-mcp-go.git
cd perplexity-mcp-go
- Build the application:
go build -o perplexity-search-mcp
Running Locally
- Set your Perplexity API key:
export PERPLEXITY_API_KEY="your-api-key-here"
- Run the server:
./perplexity-search-mcp
Integrating with Claude
-
Copy the provided
claude_desktop_config.jsonto your Claude configuration directory:- Windows:
%USERPROFILE%\AppData\Roaming\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
- Windows:
-
Edit the configuration file to include your API key:
{
"mcpServers": {
"perplexity-search": {
"command": "/path/to/perplexity-search-mcp",
"env": {
"PERPLEXITY_API_KEY": "your-api-key-here"
}
}
}
}
Docker Support
- Build the Docker image:
docker build -t perplexity-search-mcp:latest .
- Run the container:
docker run -i --rm -e PERPLEXITY_API_KEY=your-api-key-here perplexity-search-mcp:latest
Example Usage
Once configured, Claude can use the perplexity_search tool via MCP to perform real-time web searches.
Example search with parameters:
{
"query": "latest AI research developments",
"search_recency_filter": "week",
"temperature": 0.5,
"return_related_questions": true,
"web_search_options": {
"search_context_size": "high"
}
}
Troubleshooting
If you encounter issues:
- Verify your API key is correctly set
- Check network connectivity
- Examine stderr logs for error messages
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
- Model Context Protocol for the MCP specification
- MCP-Go for the Go MCP implementation
- Perplexity for their search API
เซิร์ฟเวอร์ที่เกี่ยวข้อง
Zenn Articles
A server for searching articles on the Zenn blogging platform.
Langflow Document Q&A Server
A document question-and-answer server powered by Langflow.
Serpstat MCP Server
SEO analysis using the Serpstat API.
EzBiz Social Media Analytics
AI-powered social media profile analysis, engagement scoring, trend detection, and hashtag research.
General MCP Server
An MCP server providing search capabilities for Reddit, YouTube, and Twitter.
Tavily Search
A search API tailored for LLMs, providing web search, RAG context generation, and Q&A capabilities through the Tavily API.
DuckDuckGo Search
Perform web searches using the DuckDuckGo API, with features for fetching and parsing content.
YouTube
Search YouTube videos and retrieve their transcripts using the YouTube API.
MCP Deep Research
Performs deep web searches for information using the Tavily API.
Secondhand MCP
Connects AI to Facebook Marketplace, Ebay, Poshmark, and Depop to find you the best deals