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    A Model Context Protocol server providing security vulnerability intelligence tools including CVE lookup, EPSS scoring, CVSS calculation, exploit detection, and Python package vulnerability checking.
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    MIT
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    Enables AI assistants to send SMS messages, verify phone numbers via OTP, assess fraud risk, and access TeleSign API documentation through natural language.
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    Apache 2.0
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    A Python MCP server for SonarQube, enabling AI agents to query projects, issues, quality gates, coverage, and security hotspots.
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    MIT
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    Analyzes application code locally to automatically generate baseline AWS IAM identity-based policies by detecting AWS SDK calls in Python, Go, and TypeScript applications. Helps AI coding assistants quickly create IAM permissions that can be refined as applications evolve.
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    Apache 2.0
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    Enables AI assistants to search and retrieve information from the REMnux malware analysis toolkit documentation, allowing users to ask questions about reverse-engineering tools and get accurate, up-to-date answers from the live documentation.
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    A local security knowledge base that indexes documentation like CVEs and CWEs using hybrid keyword and semantic search. It enables LLM agents to query indexed materials via MCP for accurate, offline retrieval during security audits and code reviews.
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    MIT
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    Deploy Python functions as authenticated MCP connectors for Claude.ai and other MCP hosts, with pluggable OAuth and support for separate venvs for heavy dependencies.
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    Apache 2.0
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    Project Point One Percent - Agent Pay \[pop-pay] is a payment guardrail and one-time flow protocol specifically designed for Agentic AI (e.g., Claude Code, OpenClaw). It enables agents to handle financial transactions safely without risking unlimited exposure of human-controlled credit cards.
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    MIT
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    Enables AI agents to securely manage API keys and secrets via the MCP protocol, with encrypted storage at rest and a simple CLI and Python SDK.
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    MIT
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    An MCP server that provides tools for deterministic EU AI Act risk classification and documentation generation, enabling human-in-the-loop AI system assessments inside Claude Code.
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    MIT
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    Provides real-time content safety protection for large language models by detecting and preventing risks in both input and output content across multiple dimensions including compliance, ethics, and security.
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    MIT