Run MCP Action

Action ID: mcp_run_action

Description

Run any action on MCP.

Connection

Name	Description	Required	Category
MCP Connection	The MCP connection to use for the action.	True	mcp

Input Parameters

Name	Type	Required	Default	Description
action	string	✓	-	The name of the action to run on MCP
input_params	object	✓	-	Input parameters for the action (varies by action)

View JSON Schema

{
  "description": "Run MCP run action node input.",
  "properties": {
    "action": {
      "description": "The action to run. This is the name of the action to run.",
      "title": "Action",
      "type": "string"
    },
    "input_params": {
      "additionalProperties": true,
      "description": "The input parameters for the model. These vary depending on the model you're using. Check the model's documentation for details.",
      "title": "Input Parameters",
      "type": "object"
    }
  },
  "required": [
    "action",
    "input_params"
  ],
  "title": "MCPRunActionInput",
  "type": "object"
}

Output Parameters

Name	Type	Description
success	boolean	Whether the MCP action was successful
result	any	The output from the MCP action (varies by action)
error	string	Error message if the action failed (null if successful)

View JSON Schema

{
  "description": "Output from a MCP run action.",
  "properties": {
    "error": {
      "anyOf": [
        {
          "type": "string"
        },
        {
          "type": "null"
        }
      ],
      "default": null,
      "description": "The error from the MCP action.",
      "title": "Error"
    },
    "success": {
      "description": "Whether the MCP action was successful.",
      "title": "Success",
      "type": "boolean"
    },
    "result": {
      "description": "The output from the FAL model. This can be text, URLs to generated images, or other data depending on the model.",
      "title": "Result"
    }
  },
  "required": [
    "success",
    "result"
  ],
  "title": "MCPRunActionOutput",
  "type": "object"
}

How It Works

This node provides a generic interface to execute any action available on the MCP (Model Context Protocol) platform. You select an action by name from the available options, provide the required input parameters as a JSON object, and the node executes that action through your configured MCP connection. The response includes success status, result data, and error information if applicable. This flexible approach allows you to access various MCP capabilities without needing separate nodes for each action.

Usage Examples

Example 1: Run Text Generation Action

Input:

action: "text-generation"
input_params: {
  "prompt": "Write a product description for wireless headphones",
  "max_length": 150
}

Output:

success: true
result: "Premium wireless headphones with active noise cancellation..."
error: null

Example 2: Run Image Processing Action

Input:

action: "image-enhance"
input_params: {
  "image_url": "https://example.com/photo.jpg",
  "enhancement_type": "upscale",
  "factor": 2
}

Output:

success: true
result: {
  "enhanced_image_url": "https://mcp.com/enhanced/photo.jpg",
  "dimensions": "3840x2160"
}
error: null

Example 3: Run Data Analysis Action

Input:

action: "sentiment-analysis"
input_params: {
  "text": "This product exceeded my expectations!",
  "language": "en"
}

Output:

success: true
result: {
  "sentiment": "positive",
  "confidence": 0.95
}
error: null

Common Use Cases

• AI Model Execution: Run various AI models available on MCP for text, image, or audio processing

• API Gateway: Use MCP as a unified gateway to multiple third-party services and models

• Dynamic Action Selection: Programmatically choose which MCP action to run based on workflow logic

• Model Comparison: Execute the same operation across different models to compare results

• Batch Processing: Run multiple MCP actions sequentially or in parallel within a workflow

• Custom Integrations: Access specialized MCP actions for specific business requirements

• Prototyping: Quickly test different MCP capabilities without committing to specific implementations

Error Handling

Error Type	Cause	Solution
Connection Failed	Invalid or missing MCP connection credentials	Verify your MCP connection is properly configured with valid credentials
Action Not Found	Specified action name doesn't exist on MCP	Check the available actions list and verify the action name spelling
Invalid Parameters	input_params missing required fields or wrong types	Review the action's documentation for required parameter structure
Authentication Error	MCP API key expired or invalid	Update your MCP connection with a valid API key
Rate Limit Exceeded	Too many requests to MCP in short period	Implement delays between requests or upgrade your MCP plan
Timeout Error	Action execution exceeded time limit	Simplify the request or increase timeout settings if available
Insufficient Credits	MCP account has insufficient credits for the action	Add credits to your MCP account or reduce action usage

Notes

• Action-Specific Parameters: Each MCP action has its own parameter requirements. Consult MCP documentation for specific action details.

• Dynamic Discovery: The action dropdown is populated from your MCP connection, showing only available actions for your account.

• Error Checking: Always check the success field in the output before using the result data.

• Parameter Validation: The input_params must be valid JSON. Validate your JSON structure before execution.

• Result Structure: The result field structure varies by action. Handle different result types appropriately in subsequent nodes.

• Cost Management: Different MCP actions have different costs. Monitor your usage to control expenses.

• Version Compatibility: Ensure your MCP connection version is compatible with the actions you're trying to run.

• Async Operations: Some MCP actions may run asynchronously. Check the action documentation for completion handling.