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    缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台,致力于通过代理AI技术减少人力成本,高效高精度为用户提供分钟级接入的内容风控解决方案,破解安全威胁,提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel
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    MIT
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    A secure tool-execution plane for agentic AI that enforces JWT authentication, rate limiting, prompt-injection inspection, and audit logging, while ingesting downstream OpenAPI endpoints as MCP tools.
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    MIT
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    SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.
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    MIT
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    Scan any project or website for privacy compliance issues directly in your AI coding tool. Detects tracking tech, cookies, and third-party data collection. Works in Claude Code, Cursor, and Windsurf.
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    MIT
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    Enables AI assistants to read live macOS processes and identify monitoring software, including Chinese enterprise EDR/DLP/MDM tools, through a read-only MCP server.
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    MIT
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    The accountability layer for AI agents — a named human's signed yes before an agent does anything irreversible (payment, record change, deploy), then an offline-verifiable Trust Receipt. Apache-2.0, formally verified.
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    Apache 2.0
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    Mandatory human approval gate for autonomous AI agents. Before any critical, irreversible, or financially significant action executes — file deletion, production deployment, financial transaction — the agent calls oracle_validate. A human receives a real-time Telegram notification with full context and taps Approve or Reject. The agent waits for the decision before proceeding.
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    A tool for detecting and cleaning Java memory shells via local or SSH remote execution. It enables AI agents to scan Java processes, analyze suspicious class code, and safely remove memory shells after user confirmation.
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    MIT
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    Enables AI assistants to execute malware analysis tools on a REMnux system via Docker, SSH, or local connections. It provides automated file-type analysis, structured tool discovery, and security guardrails for streamlined malware investigation.
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    GPL 3.0
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    Enables LLMs to perform software composition analysis including license detection, vulnerability assessment, SBOM generation, and policy validation using the SEMCL.ONE toolchain.
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    Apache 2.0
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    Local guardrail proxy for AI coding agents. Wraps any MCP server (stdio or HTTP/SSE) and blocks destructive tool calls before they execute, with TOFU catalog pinning against rug pulls and tool-poisoning/result-injection scanning. Single Rust binary, Apache-2.0.
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    Apache 2.0
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    Analyzes GitHub Pull Request diffs for security vulnerabilities and data leaks, using a deterministic filter to skip trivial changes and an AI-powered analysis for logic changes.
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    MIT