Jenkins CI/CD
Jenkins MCP server implementation by Ashwini Ghuge that provides AI assistants with complete access to Jenkins CI/CD operations through comprehensive job management, build monitoring, and pipeline execution capabilities. Built with Python using FastMCP and featuring a multi-tier intelligent caching system, the implementation supports triggering jobs with parameter processing, real-time build status tracking, console log access, artifact management, and batch operations with priority queuing. The server includes advanced features like smart caching that differentiates between running and completed builds, CSRF protection with automatic crumb handling, nested job support for Jenkins folder structures, and pipeline stage-by-stage execution tracking, making it valuable for DevOps teams managing complex CI/CD workflows, developers needing programmatic Jenkins access for build automation, and organizations requiring AI-assisted monitoring and management of their Jenkins infrastructure.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- devops-ci
- Source
- PulseMCP
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Jenkins CI/CD from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.