| name | jenkins-mcp-connector |
| description | MCP connector for Jenkins CI/CD – enables AI-powered build management, pipeline configuration, and job administration through Claude |
| license | MIT |
| tags | ["dev","ci-cd","mcp","jenkins","automation"] |
| difficulty | advanced |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Jenkins MCP Connector
Overview
This skill enables Claude to interact with Jenkins through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Jenkins's REST API, allowing natural language control of Jenkins operations, intelligent automation, and AI-powered assistance for Jenkins workflows.
When to Use This Skill
- Jenkinsfile and pipeline creation via natural language
- Build trigger and parameter configuration
- Build log analysis and failure diagnosis
- Plugin management and configuration
- Job and folder organization
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Jenkins │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Jenkins operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/json, /job/:name/build, /job/:name/config.xml, /pluginManager/api, /queue/api
Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "jenkins-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Jenkins resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
const response = await fetch(`${BASE_URL}/api/json`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
: [{ : , : .(data, , ) }],
};
}
);
server.(
,
,
{
: z.().(),
: z.({}).().().(),
},
({ name, config }) => {
response = (, {
: ,
: {
: ,
: ,
},
: .({ name, ...config }),
});
data = response.();
{
: [{ : , : }],
};
}
);
server.(
,
,
{
: z.().(),
: z.().().(),
},
({ , timeframe }) => {
response = (, {
: { : },
});
data = response.();
{
: [{ : , : .(data, , ) }],
};
}
);
transport = ();
server.(transport);
Claude Desktop Configuration
{
"mcpServers": {
"jenkins-mcp-connector": {
"command": "node",
"args": ["path/to/jenkins-mcp-connector/index.js"],
"env": {
"JENKINS_API_KEY": "your-api-key",
"JENKINS_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Jenkins API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Jenkins API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Create a multi-branch pipeline for the microservice with build, test, and deploy stages"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
Changelog
| Version | Date | Changes |
|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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