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.

Frida MCP is an MCP protocol implementation based on the Frida dynamic detection toolkit, providing AI systems with the ability to interact with mobile and desktop applications.

AIM Guard MCP is an AI security protection server that provides security analysis, content detection, and protection instruction tools for AI agents to protect the security of MCP interactions.

MCP Fortress is a comprehensive security tool designed for Model Context Protocol (MCP) servers, offering automated vulnerability scanning, runtime protection, risk scoring, and threat detection functions, and supporting integration with AI assistants such as Claude Code through the MCP server mode for security analysis.

VkRunner is a Vulkan shader testing tool based on Piglit's shader_runner, aiming to support test scripts as similar as possible to Piglit's shader_test format. It supports writing shaders in GLSL or SPIR-V and provides a rich set of test commands to verify shader behavior, including drawing, computing, and probe detection functions.

MCP Server Semgrep is a server that complies with the Model Context Protocol standard, integrating the Semgrep static analysis tool with an AI assistant to provide code security analysis, quality improvement, and vulnerability detection functions. The project simplifies the architecture design, supports multi - platform operation, can be installed in multiple ways, and provides a rich set of code analysis functions.

A Java source code vulnerability auditing tool based on function-level taint analysis. It provides security analysis capabilities for AI assistants through the MCP protocol, supporting the detection of multiple vulnerability types and call chain tracing.

The AI-Cursor-Scraping-Assistant is a web scraper generation tool based on Cursor AI and the MCP protocol. It can quickly analyze website structures and automatically generate Scrapy or Camoufox scraper code. The project consists of two major components: Cursor rule sets and MCP tool sets. It supports scraping e-commerce PLP/PDP pages and has anti-bot detection and bypass capabilities.

The MCP Dual Cycle Reasoner is a metacognitive enhancement tool designed for autonomous AI agents. Through a dual-cycle framework (sentinel monitoring and arbiter management), it enables anomaly detection and experience learning to enhance the self-awareness and reliability of agents.

The GitHub MCP server provides AI-assisted tools such as code review, PR analysis, and security detection, and supports local and Docker deployment.

The MCP Probe Kit is a powerful development toolset that provides 23 practical tools, covering the entire process of code quality detection, development efficiency improvement, and project management. It is specifically designed for Cursor AI to help developers improve development efficiency and quality.

This is an MCP server implemented for the VictoriaMetrics anomaly detection tool vmanomaly, which allows AI assistants to directly interact with the vmanomaly REST API through the protocol, enabling functions such as health checks, model management, configuration generation, and documentation search.

Omen is an AI code analysis CLI tool that provides codebase context for AI assistants through multiple metrics such as complexity analysis, technical debt detection, dependency graph, and hotspot analysis, helping to predict defects and identify risks.

The OpenCV MCP Server is a Python - based computer vision service that provides OpenCV's image and video processing capabilities through the Model Context Protocol (MCP). It offers a full set of computer vision tools from basic image processing to advanced object detection for AI assistants and language models, including image processing, edge detection, face recognition, video analysis, and real - time object tracking.

The Behavioural Prediction MCP Server provides AI-driven blockchain wallet behavior prediction, fraud detection, and exit scam prediction tools to help protect the security of DeFi users and evaluate the credibility of wallets and contracts.

This project provides a series of KQL queries to detect abuse behaviors related to the BloodHound BARK toolkit in Azure AD tenants. These queries aim to identify behaviors simulated by BARK rather than the use of the tool itself. The content includes detection queries for different BARK functions, control suggestions, and relevant resource links.

Fork Parity MCP is an enterprise-level branch synchronization management tool that provides AI-driven commit analysis, automated conflict detection, and GitHub Actions integration to help teams efficiently maintain the synchronization of branches in upstream repositories.

The behavior prediction MCP server provides AI-driven tools for analyzing wallet behavior prediction, fraud detection, and rug pull scam prediction, helping to protect DeFi users and monitor liquidity risks.