What AI providers are supported?
Supported providers include Claude 4/3 (Opus & Sonnet), GPT-4o/4, Google Gemini Pro/Flash, OpenRouter (100+ models), DeepSeek (reasoning models), and local models via Ollama.
@Louranicas
基本信息
Claude-Optimized Deployment Engine (CODE) - AI-powered infrastructure automation platform with Rust-accelerated Circle of Experts system. Features 20x performance boost, 11 MCP servers, 51+ tools, and comprehensive security hardening. 85-90% complete.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"claude-optimized-deployment": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
Claude-Optimized Deployment Engine (CODE) is a production-ready AI-powered infrastructure automation platform with comprehensive MCP (Model Context Protocol) integration and Rust-accelerated performance. It provides multi-AI consultation via the Circle of Experts system and automates deployment pipelines across Docker, Kubernetes, Azure, and other cloud services through 11 MCP servers with 51+ tools. It is designed for DevOps engineers and teams seeking automated, AI-driven deployment and operations.
Clone the repository, run make dev-setup or manually set up a Python virtual environment, install requirements, and optionally build Rust performance modules with make rust-build. Configure at least one AI provider API key (e.g., ANTHROPIC_API_KEY) and optional MCP server credentials (e.g., AWS_ACCESS_KEY_ID, SLACK_BOT_TOKEN). Use the provided Python examples or integrate the SDK into your own scripts to invoke Circle of Experts consultations and MCP deployment automation.
Supported providers include Claude 4/3 (Opus & Sonnet), GPT-4o/4, Google Gemini Pro/Flash, OpenRouter (100+ models), DeepSeek (reasoning models), and local models via Ollama.
Python 3.10+, at least one AI API key (Anthropic, OpenAI, Google, etc.), and Docker (for container automation). The Rust toolchain is optional but recommended for performance modules. Kubernetes cluster and cloud provider credentials are optional for full infrastructure automation.
Set environment variables for the required MCP servers: e.g., `AWS_ACCESS_KEY_ID` for S3, `SLACK_BOT_TOKEN` for Slack notifications, and `AZURE_DEVOPS_TOKEN` for Azure DevOps integration.
Yes. The project reports 95%+ completion with production deployments verified. It has passed 9 security audits and includes real-time monitoring, alerting, and team integration. Minor features like advanced GitOps and canary deployments are planned for v1.1.
No, Rust is optional. The core Python functionality works without it, but building the Rust performance modules (`make rust-build`) provides 2–20x speed improvements for consensus, aggregation, and pattern analysis.
A docker MCP Server (modelcontextprotocol)
YesTechie builds enterprise UniFi networks, cameras, access control, cabling and Wi-Fi for businesses nationwide from its California HQ. Agents can read real project case studies and practical configuration guides, price
Deploy and manage SnapDeploy apps (Docker containers on AWS) from Claude Code, Cursor, Codex or Gemini CLI: builds, logs, env vars, add-ons, domains.
Model Context Protocol (MCP) server for Kubernetes and OpenShift

Build and run websites, APIs, automations, and admin tools from chat. Your agent creates the data, logic, pages, and scheduled jobs; Tessryx hosts them on your own domain. No code generated, nothing to deploy.
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