Agent-ready DevOps, security, infrastructure, and compliance knowledge base with 80+ skills across Kubernetes, Terraform, AWS/Azure/GCP, AI platform operations, container hardening, SOC2/ISO27001, and incident response—plus ready-to-run scripts, templates, and playbooks for SRE, platform, and security teams.
Production-ready plugins for SAP development with AI coding assistants — BTP, CAP, Fiori, ABAP, HANA, Analytics Cloud, Datasphere, and more
C++ MCP SDK - build Model Context Protocol (MCP) servers and clients in C++ / CPP. Enterprise-grade security, observability, connectivity. Stdio, HTTP+SSE, Streamable HTTP, WebSocket, TCP transports. Bindings for Python, TypeScript, Go, Rust, Java, C#.
secure multiplexed execution paths for agents - zero trust, zero setup, zero latency.
Model Context Protocol (MCP) server for pfSense firewall management. Control firewall rules, VPNs, DNS, DHCP and diagnostics in natural language from Claude Desktop, Claude Code or any MCP client — 333 wire-format-verified tools for the pfSense REST API, with safety guardrails, config backup and rollback on every change.
Astrid is a portable, capability-secure operating system for composable software.
Securely scale AI usage across your organization. A single stack to Connect, Secure, Observe and Distribute agents, MCPs, and Skills within your company.
Enterprise AI bastion host for secure AI API and MCP access, with unified proxying, RBAC, audit logs, rate limiting, and cost tracking across OpenAI, Anthropic, Gemini, and self-hosted LLMs.
MCP Fusion - The TypeScript framework for secure MCP servers.
Portable , scalable , secure AI Agents
lunar.dev: Agent native MCP Gateway for governance and security
The Model Context Protocol (MCP) is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.
Customer-run client for Secure MCP Tunnel: connect private or localhost MCP servers to ChatGPT, Codex, the Responses API, and AgentKit without exposing them to the public internet.
Run AI coding agents in hardened container sandboxes.
A curated, DevOps-focused list of Model Context Protocol (MCP) servers—covering source control, IaC, Kubernetes, CI/CD, cloud, observability, security, and collaboration—with a bias toward maintained, production-ready integrations.
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。
Govern consequential AI agent actions in Docker with deterministic policy, human approval, and signed Decision Dossiers.
A simple, secure MCP-to-OpenAPI proxy server
Local-first MCP password and credential manager for AI agents. Use passwords, API keys, SSH identities, and TOTP without exposing hidden plaintext to the model.
A set of MCP security checklists and guides for agents and MCP servers.
Skill engineering methodology and publishing pipeline for AI agent skills. Validates structure, scans for security, audits entire projects, and publishes to GitHub. Skills are code — engineer them like it.
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.
Production-Ready MCP Server Framework • Build, deploy & scale secure AI agent infrastructure • Includes Auth, Observability, Debugger, Telemetry & Runtime • Run real-world MCPs powering AI Agents
Supercharge AI Agents, Safely