The Perplexity MCP Server is an intelligent research assistant that uses Perplexity's AI model to automatically analyze query complexity and select the best model to process requests. It supports three tools: search, reasoning, and in - depth research.

The 302AI BrowserUse MCP Server is an AI-based browser automation server that enables natural language control of browsers and web research through the Model Context Protocol (MCP).

The Perplexity MCP Server is an intelligent research assistant that uses Perplexity's AI model to provide automatic query complexity detection and optimal model routing functions, supporting three tools: search, reasoning, and in - depth research.

Awesome MCP Servers is a comprehensive collection of Model Context Protocol (MCP) servers, covering 7,158 MCP servers divided into 33 categories, including AI integration, art and media, browser automation, cloud services, databases, developer tools, file systems, finance, gaming, hardware, healthcare, infrastructure, knowledge management, location maps, marketing, monitoring, multimedia processing, operating systems, project management, scientific research, security, social media, travel and transportation, utilities, and version control, etc.

JADX is a powerful decompilation tool for Android Dex and Apk files. It supports converting Dalvik bytecode into Java source code, decoding resource files, and restoring code obfuscation. It provides two operation modes: command-line and graphical interface, and is suitable for developers and security researchers.

Intelligent stock data service based on Model Context Protocol, providing real-time quotes, fundamental analysis, news, and in-depth research reports driven by AI for A-shares, Hong Kong stocks, and US stocks

A deep research MCP service based on Ollama, realizing automated web search and knowledge synthesis through local LLM models

The BioContextAI Knowledge Base MCP is a model context protocol server designed for biomedical research that provides a standardized connection layer between AI systems and biomedical resources, supporting integrated access to multiple biomedical databases and tools.

This project is a research and documentation on the Model Context Protocol (MCP), including technical analysis, implementation solutions, usage guides, and other resources, aiming to comprehensively introduce the MCP ecosystem.

Octagon MCP is a market data model context protocol server that integrates the Octagon market intelligence API, providing AI agent services for public market data, private market data, and deep research.

The PubMed MCP Server is an interface service based on the Model Context Protocol, providing comprehensive access to the PubMed biomedical literature database for AI agents and research tools. It supports functions such as literature search, metadata acquisition, citation analysis, research plan generation, and data visualization, and is efficiently integrated through the NCBI E - utilities API.

The AMiner academic search server based on the Model Context Protocol provides functions for paper keyword, journal, and author search, as well as an AI research assistant.

OpenDeepSearch is an open - source research tool and an alternative to Perplexity Deep Research. It provides in - depth search and research capabilities through the Model Context Protocol (MCP). It can break down complex problems into sub - problems, perform multiple rounds of searches using the Brave Search API, analyze the results, and generate structured research reports. It supports citation of sources and can be integrated into MCP clients such as Claude Desktop and Cursor.

This project is a deep research server based on the Ollama local large - model, providing automated research tools through the MCP protocol, capable of iterative search, analysis, and summarization of complex topics.

The OpenRouter Agents MCP Server is a research agent server based on the Model Context Protocol (MCP). It uses Claude 3.7 Sonnet as the planning agent to coordinate multiple OpenRouter models to decompose and execute complex research tasks, providing efficient and reliable AI research services.

The ChuckNorris MCP Server is an enhanced prompt tool designed for large language models. It uses dynamic mode adaptation technology to bypass security restrictions and is mainly used for security research and evaluation purposes.

ResearchMCP is a research tool that combines the Model Context Protocol (MCP) with multiple search engines, aiming to provide research capabilities similar to ChatGPT DeepResearch.

An intelligent research assistant integrating Perplexity AI, providing functions such as search, document retrieval, API discovery, and code modernization check, supporting context tracking and efficient API management.

The Vectorize MCP Server is a model context protocol server integrating the Vectorize service, providing functions such as vector retrieval, text extraction, and in - depth research.

Paperclip is a Model Context Protocol (MCP) server that supports searching for and retrieving research papers from Arxiv, the Open Science Framework (OSF) API, and OpenAlex.

MCPwner is a security research automation server based on the Model Context Protocol, integrating multiple security testing tools (SAST, SCA, secret scanning, etc.) to provide a unified interface for LLM - driven security analysis workflows.

HydraMCP is a lightweight and scalable network security toolkit that connects AI assistants with security tools through the Model Context Protocol (MCP), supporting AI - assisted security research, scanning, and analysis.

DeepResearch MCP is an intelligent research assistant based on the Model Context Protocol (MCP), providing comprehensive research support through automatic web search, content analysis, and structured report generation.

Zotero MCP is a tool that connects the Zotero research library with AI assistants such as Claude. It realizes functions such as paper search, summary generation, citation analysis, and PDF annotation extraction through the Model Context Protocol.

A data analysis and research MCP server based on the Gemini Flash 2 AI model, providing functions such as data parsing, intelligent analysis, report generation, and automatic email sending.

Perplexity Deep Research MCP is a Model Context Protocol server that provides web search functionality for the Perplexity AI API, supporting AI assistants to perform web searches using the sonar - deep - research model.

This project guides developers on how to integrate the MCP service with GitHub Copilot to extend the capabilities of the AI-assisted development workflow. Through less than an hour of learning, users will set up the GitHub MCP server, implement Copilot proxy mode integration, and complete the full process practice from issue research to code submission.

This project is a collection of resources related to the security of the Model Context Protocol (MCP), including research papers, security vulnerability analyses, tools, articles, and other relevant resources. It aims to help developers and security experts understand and address security challenges in the MCP protocol.

Gemini DeepSearch MCP is an automated research agent that uses the Google Gemini model and Google Search for in-depth multi-step web research and generates high-quality, referenced answers.

The NOAA Tides & Currents MCP Server provides tools for fast access to NOAA ocean and atmospheric data, including tide, current, meteorological, astronomical, and climate research data. It supports multiple transport modes and integration methods.

A data analysis and research MCP server based on the Gemini Flash 2 AI model, providing functions such as data parsing, statistical analysis, research report generation, and automatic email sending.

The QuantConnect MCP Server is a localized model context protocol server designed for quantitative trading, providing complete integration with the QuantConnect platform, including research environment, statistical analysis, portfolio optimization, etc. It supports quantitative strategy development through natural - language interaction with an AI assistant.

The ClinicalTrials.gov MCP server is an interface service based on the Model Context Protocol that provides access to the official ClinicalTrials.gov database, supporting AI agents and LLMs to programmatically search, retrieve, and analyze clinical research data.

Deep Research MCP is a server project based on the Model Context Protocol (MCP), aiming to conduct comprehensive network research through Tavily's search and crawl APIs and integrate the data into structured Markdown documents to support high - quality content generation for large - language models (LLMs).

ThinkingCap is a multi-agent research server based on the model context protocol that can run multiple LLM providers in parallel and synthesize their responses to achieve comprehensive multi-angle analysis.

A modern MCP server implementation that provides web search and research paper analysis functions for AI assistants through the Brave Search API and Google's Gemini model.

The Adzuna Jobs MCP Server is a service based on the Model Context Protocol (MCP) that provides access to the Adzuna recruitment search API, supporting job search, salary data analysis, and employer information research in 12 countries.

The Propbar MCP Server provides UK property research tools, enabling AI assistants to search for properties, analyze area safety, find nearby schools, explore demographic data, and build an automated valuation model, covering data on over 30 million UK properties.

An MCP server designed for quantitative research, used to manage the research knowledge graph and support the structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.

NeoCoder is an AI programming assistance system based on the Neo4j knowledge graph. It enables the interaction between AI assistants and the knowledge graph through an MCP server, providing standardized coding workflows, dynamic instruction manuals, and project memory functions. The system supports multiple operation modes (incarnations), including basic programming, scientific research, decision - making analysis, complex system modeling, knowledge graph management, and code analysis. It stores workflow templates and execution records in Neo4j to ensure the traceability and standardization of the coding process.