Install
$ agentstack add mcp-0xhumban-perplexity-mcp Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.
Security review
⚠ Flagged1 finding(s); flagged for manual review. · v0.1.0 How review works →
- • Prompt-injection patterns
- • Secret / credential exfiltration
- • Dangerous shell & filesystem operations
- • Untrusted network calls
- • Known-malicious package signatures
- high Pipes remote content directly into a shell (remote code execution).
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
perplexity-mcp
A Perplexity AI MCP (Model Context Protocol) server implementation that enables AI assistants to search the web and get real-time information through Perplexity's Sonar models.
Motivation
This project was created to utilize the $5 credits from Perplexity's Pro plan (free for students: perplexity link), providing an easy way to access web search capabilities through MCP-compatible AI assistants.
Features
- 🌐 Web search capabilities through Perplexity AI
- 🔍 Multiple Sonar models support (sonar, sonar-pro, sonar-deep-research, sonar-reasoning, sonar-reasoning-pro)
- 🚀 Easy integration with VS Code and other MCP clients
- 📚 Citation support for sources
Prerequisites
- Python 3.12 or higher
- UV package manager
- Perplexity API key (Get one here)
Installation
Method 1: No Installation Required (Recommended)
You can run perplexity-mcp directly without any installation using uv tool run. Just install UV and configure VS Code (see Configuration section below) - uv will handle everything automatically!
# Install UV package manager first
curl -LsSf https://astral.sh/uv/install.sh | sh # macOS/Linux
# or
brew install uv # macOS with Homebrew
Method 2: Development Install
For development or to contribute:
1. Install UV Package Manager
# macOS (Homebrew)
brew install uv
# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
# macOS/Linux (Direct)
curl -LsSf https://astral.sh/uv/install.sh | sh
2. Clone the repository
git clone https://github.com/0xHumban/perplexity-mcp.git
cd perplexity-mcp
3. Install dependencies
uv sync
Configuration
For VS Code
>NOTE: To add it globaly: Create / Update the gloabl config file: ~/.config/Code/User/mcp.json
If you used Method 1 (No Installation - Recommended):
Create or edit .vscode/mcp.json in your workspace:
{
"inputs": [
{
"type": "promptString",
"id": "perplexity-key",
"description": "API Key for Perplexity AI",
"password": true
}
],
"servers": {
"perplexity-mcp": {
"command": "uv",
"args": [
"tool", "run", "--from",
"git+https://github.com/0xHumban/perplexity-mcp.git",
"perplexity-mcp"
],
"env": {
"PERPLEXITY_API_KEY": "${input:perplexity-key}"
}
}
}
}
This method runs the tool directly from GitHub without any prior installation!
If you used Method 2 (Development Install):
Create or edit .vscode/mcp.json in your workspace:
{
"inputs": [
{
"type": "promptString",
"id": "perplexity-key",
"description": "API Key for Perplexity AI",
"password": true
}
],
"servers": {
"perplexity-mcp": {
"command": "uv",
"args": [
"run",
"perplexity-mcp"
],
"cwd": "/path/to/perplexity-mcp",
"env": {
"PERPLEXITY_API_KEY": "${input:perplexity-key}"
}
}
}
}
Replace /path/to/perplexity-mcp with the actual path to your cloned repository.
Then:
- Reload VS Code window
- Enter your Perplexity API key when prompted
For other MCP clients
Set the environment variable:
export PERPLEXITY_API_KEY="your-api-key-here"
Then run:
uv run perplexity-mcp
Available Features
The Perplexity MCP server provides four main tools to interact with the Perplexity AI API:
1. ask_perplexity - Standard Search
Main tool for performing web searches via Perplexity AI.
How it works:
- Sends a query to Perplexity AI to get up-to-date information from the web
- Returns a formatted response with cited sources
- Uses the default model (sonar) unless otherwise specified
Use cases:
- Search for recent or real-time information
- Get answers based on multiple web sources
- Verify facts or current statistics
Example:
#ask_perplexity
What are the latest AI developments in October 2024?
2. ask_perplexity_exact_response - Unmodified Response
Returns the exact response from Perplexity AI without any modification or reformatting.
How it works:
- Similar to
ask_perplexitybut preserves Perplexity's original response - No additional processing is applied
- Ideal when you want Perplexity's raw answer
Use cases:
- When you want to see exactly what Perplexity responded
- To avoid any interpretation or reformatting by the assistant
- Get citations and sources exactly as Perplexity provides them
Example:
#ask_perplexity_exact_response
Search for the latest tech news in France
3. ask_perplexity_for_instructions - Instructions Mode
Designed to obtain detailed and executable instructions on a complex topic.
How it works:
- Uses a special pedagogical preprompt that guides Perplexity to provide structured instructions
- Ideal for learning or understanding technical concepts
- Returns detailed steps, code examples, and clear explanations
Use cases:
- Learn a new concept or technology
- Get a step-by-step guide to accomplish a task
- Understand complex topics with practical examples
- Generate example code with detailed explanations
Example:
#ask_perplexity_for_instructions
Create a REST API server in Go for my books database
4. ask_perplexity_to_learn - Learning Mode
Pedagogical tool specially designed for learning complex topics.
How it works:
- Uses an advanced pedagogical preprompt that structures the response to facilitate learning
- Breaks down concepts into logical steps
- Provides analogies, concrete examples, and comprehension checks
- Uses the reasoning model by default for more in-depth explanations
Response structure:
- Simple overview of the concept
- Breakdown into logical steps (3-7 steps)
- For each step: simple explanation + concrete example + commented code
- Checkpoints to verify understanding
- Summary of key points and tips to go further
Use cases:
- Learning complex computer science concepts (algorithms, data structures, etc.)
- Understanding mathematical principles
- Studying new technologies or frameworks
- Self-directed learning on technical topics
Example:
#ask_perplexity_to_learn
Teach me arithmetic coding step by step with code examples in Go
Available Sonar Models
All tools support the following models:
sonar(default for askperplexity and askperplexityexactresponse)- Fast, general-purpose search
- Good balance between speed and quality
- Ideal for most queries
sonar-pro- Enhanced accuracy and depth
- More sources and analysis
- Recommended for important searches
sonar-deep-research- Comprehensive and thorough research
- Complete analysis of multiple sources
- For serious research projects
sonar-reasoning(default for askperplexityforinstructions and askperplexitytolearn)- Advanced reasoning capabilities
- Better for complex explanations
- Ideal for learning and instructions
sonar-reasoning-pro- Premium reasoning with extended context
- Most powerful for complex tasks
- Best understanding and explanation
Development
Project Structure
perplexity-mcp/
├── perplexity_mcp/
│ ├── __init__.py
│ ├── server.py # Main MCP server implementation
│ └── cli.py
├── pyproject.toml # Project configuration
├── uv.lock # Dependency lock file
└── README.md
License
See [LICENSE](LICENSE) file for details.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Support
For issues and questions, please open an issue on GitHub.
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: 0xHumban
- Source: 0xHumban/perplexity-mcp
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.