security & testing向けの厳選されたMCPサーバーコレクションをご覧ください。1651個のサーバーを閲覧し、ニーズに最適なMCPを見つけましょう。
Automates comprehensive management and integration across the entire Microsoft 365 ecosystem via the Microsoft Graph API.
Provides safe, structured access to memory analysis and debugging functionality via the Model Context Protocol (MCP).
Provides a standardized interface for AI agents to interact with Commvault software.
Equips AI agents with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL).
Pins third-party dependencies to immutable digests using the Model Context Protocol.
Enables AI assistants to perform code quality checks, suggest improvements, and automate debugging workflows.
Cryptographically signs and verifies AI agent tool schemas to prevent supply-chain attacks.
Provides a production-ready framework for building and scaling MCP servers with features like Redis-backed state management and delegated OAuth support.
Analyzes Python code for structure, complexity, and dependencies using a Model Context Protocol server.
Retrieves CVE details from the NVD API and fetches EPSS scores to provide comprehensive vulnerability information.
Provides intelligent mobile device control and automation capabilities for Android and iOS, deeply integrated with Cursor AI.
Tests backend APIs for security vulnerabilities using a Model Context Protocol (MCP) server.
Automates GDB interactions by exposing its command interpreter as a lightweight server.
Provides read-only access to Microsoft Sentinel data for querying, incident viewing, and resource exploration, designed for use with LLMs in test environments.
Analyzes code repositories for vulnerabilities and quality issues, suggesting fixes based on Sentry error logs.
Provides network scanning functionality through a Model Control Protocol (MCP) server.
Connects MCP clients to Cortex, enabling threat intelligence analysis via tools consumable by large language models.
Enables AI models and agents to measure internet speed and network performance metrics through a standardized Model Context Protocol (MCP) interface.
Orchestrates multiple AI models for automated code review, security analysis, and multi-agent consensus within development workflows.
Enables LLMs to securely execute code via a managed code interpreter.
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