Advanced MCP tool for Perplexity and OpenRouter API integration. Supports both simple and complex queries with file attachments. Built with AI-first
Perplexity MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Advanced MCP tool for Perplexity and OpenRouter API integration. Supports both simple and complex queries with file attachments. Built with AI-first development approach using Cline, Cursor, and Wispr Flow.
For example, let's suppose we want to find out the latest version of Python. 1. You would search on Google. 2. Then read the top two or three results directly to verify.
The server ships on npm as @smithery/cli, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
You will need 2 environment variables: OPENROUTER_API_KEY, PERPLEXITY_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Plenty of monitoring and observability servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
{
"mcpServers": {
"perplexity-advanced": {
"command": "npx",
"args": ["-y", "@smithery/cli"],
"env": {
"OPENROUTER_API_KEY": "your-value",
"PERPLEXITY_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| OPENROUTER_API_KEY | Credential the server authenticates with. | Yes |
| PERPLEXITY_API_KEY | Credential the server authenticates with. | Yes |
Give your coding agent the full DevTools toolbox: traces, network, console, heap snapshots and Lighthouse.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.
Errors with full context — stack traces, issue triage and AI-powered root-cause analysis from Sentry's server.
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Automates browser interactions and enables Large Language Models (LLMs) to interact with web pages through Playwright and Chrome DevTools Protocol
Guides tool usage by providing recommendations for MCP tools at each problem-solving stage.