This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.

Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!

The memory + security kernel for AI agents. Strata: a signed append-only log, receipts on every write, exact-handle recall, memory agents can't rewrite. Operator Lite: a GuardFall-proof gate on 16 hosts.

Secure filesystem MCP server for reading, writing, searching, diffing, and patching files.

MCP Server for GitHub repository health monitoring

MCP server for JADX-AI Plugin

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Multi-account orchestration and secure token storage for OAuth-based MCP servers

MCPCAN is a centralized management platform for MCP services. It deploys each MCP service using a container deployment method. The platform supports container monitoring and MCP service token verification, solving security risks and enabling rapid deployment of MCP services. It uses SSE, STDIO, and STREAMABLEHTTP access protocols to deploy MCP。

Security infrastructure your AI can't be — deterministic, current past your model's training cutoff, whole-repo-aware, author-independent. Security MCP for vibe coding. 530 rules, 39 tools, CLI + doctor. Prompt-level shift-left security (secure_prompt — e

🔥🔒 Awesome MCP (Model Context Protocol) Security 🖥️

BloodHound-MCP-AI is integration that connects BloodHound with AI through Model Context Protocol, allowing security professionals to analyze Active Directory attack paths using natural language instead of complex Cypher queries.