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The official MCP server implementation for the Perplexity API Platform
The main features of ppl-ai/modelcontextprotocol are: AI & Machine Learning, Search and Research.
Projects with overlapping indexed features include: vectorize-io/vectorize-mcp-server — Official Vectorize MCP Server. llmquant/quant-wiki — quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering,… jina-ai/node-deepresearch — node-DeepResearch is an autonomous web research engine that uses large language models to iteratively search, read,… btahir/open-deep-research — Open-deep-research is an automated research platform that utilizes autonomous agents to perform recursive web queries… browser-act/skills — This project provides an agentic web interaction engine designed to facilitate autonomous browser automation and… aannoo/hcom — Let AI agents message, watch, and spawn each other across terminals. Claude Code, Codex, Antigravity CLI, Cursor CLI,…
Official Vectorize MCP Server
node-DeepResearch is an autonomous web research engine that uses large language models to iteratively search, read, and reason over web content to answer complex questions. It provides a chat-based interface that displays real-time reasoning steps and final answers, and can be configured to focus exclusively on academic papers by limiting searches to academic repositories. The research engine operates through an agentic search-read-reason loop that repeatedly searches, reads, and reasons until a stopping condition is satisfied. It enforces a token budget to cap total consumption and failed at
quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering, and algorithmic trading. It serves as a centralized library of documentation covering mathematical models, financial instruments, and systematic trading strategies. The project integrates AI-driven capabilities through a modular retrieval-augmented generation framework that extracts structured data from research papers and news. It features a multi-agent workflow engine designed to discover and validate predictive alpha factors, alongside tools for local large language model
This project provides an agentic web interaction engine designed to facilitate autonomous browser automation and large-scale data extraction. It serves as a framework for building and deploying agents that can navigate complex, JavaScript-rendered websites, interact with page elements, and execute multi-step workflows. By providing a structured environment for browser control, the system enables the creation of reusable automation scripts that can be deployed across diverse web platforms. The platform distinguishes itself through a comprehensive suite of security and traffic management tools,