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Automatisch MCP Server

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A Model Context Protocol (MCP) server that provides AI assistants with access to Automatisch workflow automation capabilities.

Overview

This MCP server enables AI assistants to interact with Automatisch, an open-source Zapier alternative for workflow automation. It provides tools to manage workflows, connections, executions, and app integrations.

Features

Tools Available

  • Workflow Management: Create, read, update, delete, and test workflows

  • Connection Management: Manage app connections and credentials

  • Execution Monitoring: View workflow execution history and status

  • App Discovery: Browse available apps and their capabilities

  • Testing: Test workflows with sample data

Resources Provided

  • Workflows overview with status summary

  • App connections listing

  • Available apps catalog

  • Recent executions log

Prerequisites

  • Node.js 18+

  • Running Automatisch instance

  • Automatisch API access (API key recommended)

Installation

  1. Clone or download the MCP server code

  2. Install dependencies:

    npm install
  3. Build the project:

    npm run build

Configuration

Set environment variables:

# Automatisch instance URL (default: http://localhost:3001)
export AUTOMATISCH_BASE_URL="http://your-automatisch-instance:3001"

# API key for authentication (optional but recommended)
export AUTOMATISCH_API_KEY="your-api-key"

Usage

Claude Desktop Integration

Add to your Claude Desktop configuration file:

{
  "mcpServers": {
    "automatisch": {
      "command": "npx",
      "args": ["-y", "automatisch-mcp-server"],
      "env": {
        "AUTOMATISCH_BASE_URL": "http://localhost:3001",
        "AUTOMATISCH_API_KEY": "your-api-key"
      }
    }
  }
}

Standalone Usage

npm start

Available Tools

Workflow Management

  • list_workflows - List all workflows with optional filtering

  • get_workflow - Get detailed workflow information

  • create_workflow - Create new workflow

  • update_workflow - Update existing workflow

  • delete_workflow - Delete workflow

  • test_workflow - Test workflow with sample data

Connection Management

  • list_connections - List app connections

  • create_connection - Create new app connection

Monitoring & Discovery

  • list_executions - View workflow execution history

  • get_available_apps - Browse available apps and integrations

Example Usage with AI Assistant

# List all active workflows
"Show me all active workflows"

# Create a new workflow
"Create a workflow named 'Email Notifications' that sends emails when new GitHub issues are created"

# Check recent executions
"Show me the recent workflow executions and their status"

# Get workflow details
"Tell me about the workflow with ID 'abc123'"

# List available apps
"What apps are available for integration?"

API Endpoints

The server interfaces with these Automatisch API endpoints:

  • GET /api/flows - List workflows

  • POST /api/flows - Create workflow

  • PATCH /api/flows/:id - Update workflow

  • DELETE /api/flows/:id - Delete workflow

  • GET /api/connections - List connections

  • POST /api/connections - Create connection

  • GET /api/executions - List executions

  • GET /api/apps - List available apps

Development

Running in Development Mode

npm run dev

Building

npm run build

Cleaning Build Files

npm run clean

Error Handling

The server includes comprehensive error handling:

  • Network connectivity issues with Automatisch

  • Invalid API responses

  • Missing required parameters

  • Authentication failures

Errors are logged and returned as structured responses to the AI assistant.

Security Considerations

  • Use API keys for authentication when available

  • Ensure Automatisch instance is properly secured

  • Limit network access to trusted sources

  • Regularly update dependencies

Troubleshooting

Common Issues

  1. Connection Failed: Verify AUTOMATISCH_BASE_URL is correct and accessible

  2. Authentication Error: Check AUTOMATISCH_API_KEY is valid

  3. Tool Not Found: Ensure MCP server is properly registered with Claude Desktop

  4. API Errors: Check Automatisch logs for detailed error information

Debug Mode

Enable debug logging by setting:

export NODE_ENV=development

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Make your changes

  4. Add tests if applicable

  5. Submit a pull request

License

This project is licensed under the MIT License.

Support

For issues related to:

Install Server
A
security – no known vulnerabilities
A
license - permissive license
A
quality - confirmed to work

Resources

Looking for Admin?

Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.

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