Jenkins를 위해 구축된 17개의 MCP를 찾아보세요.
Bridges Jenkins with AI language models, enabling secure and contextual interactions.
Enables AI assistants to interact with Jenkins CI/CD servers via a Model Context Protocol (MCP) interface.
Provides a robust interface to manage Jenkins CI/CD servers, enabling job triggering, build status checks, and detailed instance monitoring.
Manages Jenkins operations, enabling job listing, build triggering, and build status checks.
Integrate Jenkins CI/CD workflows and management directly into AI assistants via the Model Context Protocol.
Integrates Jenkins CI/CD functionality with Model Context Protocol (MCP) tools, enabling programmatic access for automated workflows and AI assistants.
Transforms Jenkins operations with an AI-powered natural language interface for comprehensive pipeline analysis and optimization.
Provides common operation interfaces for Jenkins jobs through a Spring AI-based MCP Server.
Optimizes Jenkins interactions for AI coding assistants, providing token-aware formatting, smart log handling, and automated failure triage.
Facilitates interaction with Jenkins CI/CD servers for managing jobs, builds, and reports.
Integrates Jenkins functionalities with an MCP server.
Manages Jenkins builds, jobs, artifacts, and queue operations via the Model Context Protocol (MCP) interface.
Integrates Cursor IDE with Jenkins CI/CD systems, enabling direct interaction through natural language commands.
Enables AI assistants to directly interact with Jenkins CI/CD systems, offering AI-powered insights, build management, and debugging.
Fetch and analyze Jenkins build logs, supporting multiple instances and automatic detection from job URLs.
Enables AI tools to interact with and control Jenkins for tasks like job triggering and status retrieval.
Streamline DevOps processes by providing multi-server management, intelligent scenario mapping, and complete CI/CD lifecycle operations for Jenkins.
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