Automatisch MCP Server
[](https://mseep.ai/app/milisp-automatisch-mcp-server)
# Automatisch MCP Server
[](https://www.npmjs.com/package/automatisch-mcp-server)
[](https://www.npmjs.com/package/automatisch-mcp-server)
[](https://bundlephobia.com/result?p=automatisch-mcp-server)
A Model Context Protocol (MCP) server that provides AI assistants with access to [Automatisch](https://github.com/automatisch/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:
```bash
npm install
```
3. Build the project:
```bash
npm run build
```
## Configuration
Set environment variables:
```bash
# 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:
```json
{
"mcpServers": {
"automatisch": {
"command": "npx",
"args": ["-y", "automatisch-mcp-server"],
"env": {
"AUTOMATISCH_BASE_URL": "http://localhost:3001",
"AUTOMATISCH_API_KEY": "your-api-key"
}
}
}
}
```
### Standalone Usage
```bash
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
```bash
npm run dev
```
### Building
```bash
npm run build
```
### Cleaning Build Files
```bash
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:
```bash
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.
## Related Projects
- [Automatisch](https://github.com/automatisch/automatisch) - Open source workflow automation
- [Model Context Protocol](https://modelcontextprotocol.io/) - Protocol specification
- [MCP SDK](https://github.com/modelcontextprotocol/typescript-sdk) - TypeScript SDK
## Support
For issues related to:
- **Issues specific to MCP Server integration or this repository**: [Open an issue here](https://github.com/milisp/automatisch-mcp-server/issues)
- **Automatisch**: Visit [Automatisch GitHub Issues](https://github.com/automatisch/automatisch/issues)
- **MCP Protocol**: Check [MCP Documentation](https://modelcontextprotocol.io/)TDQS
Scored across 10 tools
Each tool has a clearly distinct purpose targeting specific resources and actions: connections, workflows, executions, and apps. There is no overlap or ambiguity, with tools like create_workflow, update_workflow, and delete_workflow covering different lifecycle stages without confusion.
All tools follow a consistent verb_noun pattern with snake_case throughout, such as create_connection, list_workflows, and update_workflow. The naming is predictable and uniform, making it easy for agents to understand and select tools.
With 10 tools, the count is well-scoped for managing workflows, connections, and executions in an automation platform. Each tool serves a clear purpose, such as CRUD operations for workflows and monitoring executions, without being excessive or insufficient.
The toolset provides strong coverage for core workflow management, including create, read, update, delete, list, and test operations, along with connection handling and execution monitoring. A minor gap exists in lacking tools for updating or deleting connections, but agents can still perform essential tasks effectively.