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mcp-jenkins-intelligence

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.

Install / Use

claude mcp add heniv96 -- npx -y github:heniv96/mcp-jenkins-intelligence

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

78/100

Category

Automation

Supported Platforms

Claude Code
Claude Desktop
Cursor

Tags

Our assessment of mcp-jenkins-intelligence

mcp-jenkins-intelligence scores 78/100 on our quality scale, 324th of 647 Automation skills we index.

Its MCP Server is 22 KB long, well organised into 58 sections with 9 code examples: a thorough specification that gives an agent plenty to work with.

It has 3 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
3/20
Freshness
11/15

Maintenance, license and trust

  • The repository was last updated about 12 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 86/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

mcp-jenkins-intelligence compared with similar skills

All 4 of these similar skills score higher than mcp-jenkins-intelligence; compare them before choosing.

SkillScoreStarsUpdatedFormat
mcp-jenkins-intelligence (this skill)by heniv9678312mo agoMCP Server
Agent-Reachby Panniantong10085.0k8d agoCLAUDE.md
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Frequently asked questions

How do I install mcp-jenkins-intelligence?
Run claude mcp add heniv96 -- npx -y github:heniv96/mcp-jenkins-intelligence. The install tabs above show the steps for each supported agent.
Which AI agents does mcp-jenkins-intelligence work with?
It is written for Claude Code, Claude Desktop and Cursor, as a MCP Server file. Other agents that read the same format can often use it too.
Is mcp-jenkins-intelligence safe to use?
It is MIT-licensed and scores 86/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is mcp-jenkins-intelligence still maintained?
The repository was last updated about 12 months ago. That is recent enough to be usable, but agent tooling moves fast, so check the instructions against your agent's current version.

MCP Jenkins Intelligence

License Python FastMCP Jenkins MCP Stars Issues

PRs Welcome

The Jenkins Intelligence Platform
Transform your Jenkins operations with AI-powered natural language interfaces and comprehensive pipeline analysis.

Quick Start (Binary Distribution)

Prefer a ready-to-use binary? Download the latest release and start using MCP Jenkins Intelligence in seconds!

Download & Install

# Option 1: Use the installer script (recommended)
curl -fsSL https://raw.githubusercontent.com/heniv96/mcp-jenkins-intelligence/main/install.sh | bash

# Option 2: Manual download
# Download from: https://github.com/heniv96/mcp-jenkins-intelligence/releases/latest
# Choose the appropriate binary for your platform:
# - mcp-jenkins-server-macos-arm64 (macOS Apple Silicon)
# - mcp-jenkins-server-linux-amd64 (Linux AMD64)
# Make executable: chmod +x mcp-jenkins-server-<platform>

MCP Configuration

Add to your MCP client configuration (Cursor/VSCode):

{
  "mcpServers": {
    "mcp-jenkins-intelligence": {
      "command": "/path/to/mcp-jenkins-server",
      "args": [],
      "env": {
        "JENKINS_URL": "https://your-jenkins-url",
        "JENKINS_USERNAME": "your-username", 
        "JENKINS_TOKEN": "your-token"
      }
    }
  }
}

That's it! No Python installation, no dependencies - just download and run!


Overview

MCP Jenkins Intelligence is a comprehensive Model Context Protocol (MCP) solution designed for professional DevOps teams. It provides natural language interfaces for complex Jenkins pipeline operations, enabling teams to monitor, analyze, and optimize their CI/CD workflows through AI-powered conversations in VSCode and Cursor.

Key Features

Intelligent Pipeline Analysis

  • Real-time Monitoring: Live pipeline status, health metrics, and performance analytics
  • AI-Powered Insights: Natural language queries for complex pipeline analysis
  • Failure Analysis: Deep dive into pipeline failures with intelligent root cause analysis
  • Performance Optimization: Automated suggestions for improving build times and success rates
  • Advanced Analytics: Comprehensive reporting and performance comparisons
  • Anomaly Detection: AI-powered detection of unusual pipeline behavior patterns

Advanced AI Capabilities

  • Natural Language Processing: Conversational interface for complex DevOps operations
  • Smart Diagnostics: AI-driven pipeline health analysis and troubleshooting guidance
  • Context-Aware Prompts: Intelligent prompt suggestions for different analysis scenarios
  • Automated Reporting: Proactive identification of issues and optimization opportunities

Enterprise Security & Compliance

  • Multi-Authentication Support: Standard Jenkins and Azure AD integration
  • Secure Communication: TLS encryption for all Jenkins API communications
  • Audit Logging: Comprehensive audit trails for all pipeline operations
  • Minimal Privilege: Secure by design with least privilege access patterns
  • Enterprise-Grade Data Protection: 19+ protection patterns for complete data anonymization
  • Complete Anonymization: Pipeline names, cluster names, folder names, app names, branch names, organization names, repository names, and code file names are all protected
  • Hash-based Security: Sensitive data is replaced with secure hashes before AI communication
  • Local Execution: All data processing happens locally - no data leaves your environment
  • Recursive Protection: Works on nested data structures and complex objects
  • Access Control Auditing: Comprehensive permission and access control analysis

Advanced Analytics & Reporting

  • Comprehensive Reports: Generate detailed reports with metrics and insights
  • Performance Comparisons: Compare pipeline performance across teams and environments
  • Trend Analysis: Long-term performance and reliability trend analysis

Advanced AI Features

  • Anomaly Detection: AI-powered detection of unusual pipeline behavior patterns
  • Comprehensive Insights: AI-generated insights and recommendations

Performance Optimization

  • Build Time Analysis: Detailed analysis and optimization suggestions for build times

Deployment & Distribution

  • Multiple Deployment Options: Development setup or production deployment
  • Cross-Platform Support: Works on macOS, Linux, and Windows
  • Easy Configuration: Simple setup with environment variables or MCP config

Architecture

MCP Protocol Integration

The following diagram shows how MCP Jenkins Intelligence integrates with VSCode and Cursor AI through the Model Context Protocol:

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   VSCode/       │    │   MCP Protocol  │    │   Jenkins       │
│   Cursor AI     │◄──►│                 │◄──►│   Intelligence  │
│                 │    │                 │    │   Server        │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                                │
                                ▼
                    ┌─────────────────────────────────────────┐
                    │            Jenkins API                  │
                    └─────────────────────────────────────────┘
                                │
                                ▼
        ┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
        │   AI Analysis   │    │   Core Tools    │    │   MCP Resources │
        │   Engine        │    │   (30 tools)    │    │   & Prompts     │
        └─────────────────┘    └─────────────────┘    └─────────────────┘
                │                        │                        │
                ▼                        ▼                        ▼
        ┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
        │ • Health        │    │ • List          │    │ • Status        │
        │   Analysis      │    │ • Details       │    │   Resource      │
        │ • Failure       │    │ • Builds        │    │ • Summary       │
        │   Analysis      │    │ • Configure     │    │   Resource      │
        │ • AI Queries    │    │ • Test          │    │ • Dashboard     │
        │ • Metrics       │    │ • Questions     │    │   Resource      │
        │ • Dependencies  │    │ • Trigger       │    │ • Logs          │
        │ • Trends        │    │ • Stop          │    │   Resource      │
        │ • Security      │    │ • Enable/Dis    │    │ • Health        │
        │ • Export        │    │ • Config        │    │   Resource      │
        │ • Optimize      │    │ • Predict       │    │ • Analysis      │
        │                 │    │ • Suggest       │    │   Prompts       │
        └─────────────────┘    └─────────────────┘    └─────────────────┘

Modular Architecture

The internal architecture follows a clean, modular design with separation of concerns:

┌─────────────────────────────────────────────────────────────────────────┐
│                              MCP Layer                                  │
├─────────────────┬─────────────────┬─────────────────────────────────────┤
│  FastMCP Server │  Tool Registry  │  Request Router                     │
└─────────────────┴─────────────────┴─────────────────────────────────────┘
                                │
                                ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                           Modular Services                              │
├─────────────┬─────────────┬─────────────┬─────────────┬─────────────────┤
│   Models    │  Services   │  Resources  │   Prompts   │                 │
├─────────────┼─────────────┼─────────────┼─────────────┼─────────────────┤
│ • Pipeline  │ • Jenkins   │ • Status    │ • Analysis  │                 │
│ • Build     │ • Core      │ • Summary   │ • Failure   │                 │
│ • Health    │ • Control   │ • Dashboard │ • Optimize  │                 │
│ • Failure   │ • Monitor   │ • Logs      │ • Security  │                 │
│ • Query     │ • AI        │ • Health    │             │                 │
│             │ • Security  │             │             │                 │
└─────────────┴─────────────┴─────────────┴─────────────┴─────────────────┘
                                │
                                ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                         Tool Categories                                 │
├─────────────────┬─────────────────┬─────────────────┬─────────────────┤
│  Core Tools (9) │  Control Tools  │  Monitoring (4) │  AI Tools (5)   │
│                 │     (4)         │                 │                 │
├─────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ • list_pipelines│ • trigger_build │ • get_metrics   │ • Predict       │
│ • get_details   │ • stop_build    │ • dependencies  │   Failure       │
│ • get_builds    │ • enable_disable│ • monitor_queue │ • Suggest       │
│ • ask_questions │ • get_config    │ • analyze_trends│   Optimize      │
│ • configure_    │                 │                 │ • Anomaly       │
│   jenkins       │                 │                 │   Detection     │
│ • test_         │                 │                 │ • AI            │
│   connection    │                 │                 │   Insights      │
│ • analyze_      │                 │                 │ • Retry         │
│   health        │                 │                 │   Logic         │
│ • analyze_      │                 │                 │                 │
│   failure       │                 │                 │                 │
│ • get_server_   │                 │                 │                 │
│   info          │                 │                 │                 │
└─────────────────┴─────────────────┴─────────────────┴─────────────────┘
                                │
                                ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                    Additional Tool Categories                           │
├─────────────┬─────────────┬─────────────┬─────────────────────────────┤
│  Security   │ Jenkinsfile │  Analytics  │  Performance                │
│     (2)     │     (3)     │     (2)     │      (1)                    │
├─────────────┼─────────────┼─────────────┼─────────────────────────────┤
│ • scan_     │ • get_      │ • generate_ │ • analyze_                  │
│   security  │   jenkinsfile│   report   │   build_time                │
│             │ • reconstruct│ • compare_ │                             │
│             │ • suggest_  │   performance│                             │
│             │   improvements│             │                             │
└─────────────┴─────────────┴─────────────┴─────────────────────────────┘
                                │
                                ▼
┌─────────────────────────────────────────────────────────────────────────┐
│                    MCP Resources & Prompts                             │
├─

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars3
CategoryAutomation
Updated11mo ago
Forks0

Languages

Python

Trust signals

86/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

2 low