Does my Jenkins data leave my environment?
No, all data processing happens locally; sensitive data is replaced with secure hashes before any AI communication and never leaves your environment.
@heniv96
AI-powered Jenkins pipeline intelligence platform with natural language interface. Provides comprehensive pipeline analysis, failure prediction, optimization suggestions, and automated Jenkinsfile reconstruction using Model Context Protocol (MCP) integration.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-jenkins-intelligence": {
"command": "python",
"args": [
"-m",
"pytest"
]
}
}
}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。
Mcp Jenkins Intelligence is a Model Context Protocol server that provides natural language interfaces for Jenkins pipeline operations, enabling professional DevOps teams to monitor, analyze, and optimize CI/CD workflows through AI-powered conversations in VS Code and Cursor. It integrates with the Jenkins API and uses FastMCP for communication.
Download a binary release from the GitHub releases page (or use the installer script) for your platform. Add a configuration entry to your MCP client (e.g., Cursor/VS Code) with the binary path and environment variables JENKINS_URL, JENKINS_USERNAME, and JENKINS_TOKEN.
No, all data processing happens locally; sensitive data is replaced with secure hashes before any AI communication and never leaves your environment.
You need a Jenkins instance with API access and credentials; the server requires the `JENKINS_URL`, `JENKINS_USERNAME`, and `JENKINS_TOKEN` environment variables.
Download the appropriate binary for your platform (macOS, Linux, Windows) from the GitHub releases page; no Python installation or additional dependencies are needed.
Yes, it supports standard Jenkins authentication as well as Azure AD integration for enterprise environments.
It offers natural language processing for conversational queries, anomaly detection, intelligent root cause analysis for failures, and automated suggestions for optimization.
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