rundeck-mcp-server
MCP server enabling AI assistants to manage Rundeck projects, jobs, and executions through a standardized interface.
README
Rundeck MCP Server
A Model Context Protocol (MCP) server for Rundeck, enabling AI assistants to manage projects, jobs, and executions through a standardized interface.
Prerequisites
- Python 3.12+
- uv package manager
- A Rundeck instance with API access
- A Rundeck API Token (generate under User Profile > API Tokens in the Rundeck UI)
Quick Start
Install and run directly with uvx (no clone needed):
uvx rundeck-mcp --enable-write-tools
Or install from GitHub:
uv pip install git+https://github.com/justynroberts/rundeck-mcp-server.git
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
RUNDECK_API_TOKEN |
Yes | - | Rundeck API authentication token |
RUNDECK_URL |
No | http://localhost:4440 |
Rundeck server base URL |
RUNDECK_API_VERSION |
No | 41 |
Rundeck API version |
MCP Client Configuration
Claude Code
From a local clone:
git clone https://github.com/justynroberts/rundeck-mcp-server.git
claude mcp add rundeck \
-e RUNDECK_API_TOKEN=<your-api-token> \
-e RUNDECK_URL=http://your-rundeck-server:4440 \
-- uv run --directory /path/to/rundeck-mcp-server rundeck-mcp --enable-write-tools
Or add manually to ~/.claude/settings.json:
{
"mcpServers": {
"rundeck": {
"command": "uv",
"args": [
"run", "--directory", "/path/to/rundeck-mcp-server",
"rundeck-mcp", "--enable-write-tools"
],
"env": {
"RUNDECK_API_TOKEN": "<your-api-token>",
"RUNDECK_URL": "http://your-rundeck-server:4440"
}
}
}
}
From PyPI (once published):
claude mcp add rundeck \
-e RUNDECK_API_TOKEN=<your-api-token> \
-e RUNDECK_URL=http://your-rundeck-server:4440 \
-- uvx rundeck-mcp --enable-write-tools
Claude Desktop
Add to your Claude Desktop MCP configuration:
{
"mcpServers": {
"rundeck": {
"command": "uvx",
"args": ["rundeck-mcp", "--enable-write-tools"],
"env": {
"RUNDECK_API_TOKEN": "<your-api-token>",
"RUNDECK_URL": "http://your-rundeck-server:4440"
}
}
}
}
Cursor
Add to .cursor/mcp.json:
{
"mcpServers": {
"rundeck": {
"command": "uvx",
"args": ["rundeck-mcp", "--enable-write-tools"],
"env": {
"RUNDECK_API_TOKEN": "<your-api-token>",
"RUNDECK_URL": "http://your-rundeck-server:4440"
}
}
}
}
VS Code
Add to .vscode/mcp.json:
{
"servers": {
"rundeck": {
"command": "uvx",
"args": ["rundeck-mcp", "--enable-write-tools"],
"env": {
"RUNDECK_API_TOKEN": "<your-api-token>",
"RUNDECK_URL": "http://your-rundeck-server:4440"
}
}
}
}
Local Development
git clone https://github.com/justynroberts/rundeck-mcp-server.git
cd rundeck-mcp-server
uv sync --group dev
Run tests
uv run pytest
Lint and type check
uv run ruff check .
uv run pyright
Run locally
export RUNDECK_API_TOKEN=<your-token>
export RUNDECK_URL=http://localhost:4440
uv run rundeck-mcp --enable-write-tools
Available Tools
Read Tools (always available)
| Tool | Description |
|---|---|
list_projects |
List all Rundeck projects |
get_project |
Get details for a specific project |
list_jobs |
List jobs in a project with optional filtering |
get_job |
Get full job definition including options and steps |
get_execution |
Get current status of a job execution |
list_executions_for_job |
List recent executions for a job |
get_execution_output |
Get log output from an execution |
Write Tools (require --enable-write-tools)
| Tool | Description |
|---|---|
create_project |
Create a new Rundeck project |
import_job_yaml |
Import a job from YAML definition |
delete_job |
Delete a job |
run_job |
Execute a job with optional parameters |
abort_execution |
Abort a running execution |
Job Execution Workflow
The server enforces a safe execution pattern:
- Discover: Use
get_jobto retrieve the job definition and its options - Present: The AI presents option names, descriptions, defaults, required flags, and allowed values to the user
- Collect: The user provides values for required and desired optional parameters
- Execute:
run_jobis called with the collected option values - Monitor: Use
get_executionandget_execution_outputto track progress
License
MIT License - Copyright (c) fintonlabs.com
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.