Troubleshooting

​

Solution

1. Explicitly Mention Synta MCP in Your Prompt Try using a prompt like this:
   Copy

   Use synta-mcp to search for the Slack node in n8n
   
   This explicitly tells the AI to use the Synta MCP tools.
2. Restart Your AI Client
   • Completely quit your AI client (don’t just close the window)
   • Reopen the application
   • Start a new conversation/chat
3. Start a Fresh Chat
   • Previous conversations may have context that doesn’t include MCP awareness
   • Create a new chat window/conversation
   • Try your request again with explicit mention of synta-mcp
4. Verify MCP Connection
   • Check your MCP configuration is still active
   • Look for MCP indicators in your client (e.g., tool icons, MCP badge)
   • If the connection appears inactive (e.g. A red status icon on Cursor), restart your client or reconfigure following the installation steps

​

Why This Happens

​

Solution

1. Delete the MCP app from ChatGPT settings
2. Re-create the app following the installation steps
3. Repeat the process 3-5 times if it doesn’t work initially
4. This is a known ChatGPT limitation, not a Synta issue

​

Why This Happens

​

Note

​

Solution

1. Verify Synta API Key
   • Ensure you copied the full API key from synta.io/mcp
   • Check for extra spaces or newlines
   • Make sure the key starts with the correct format
2. Check N8N Credentials
   • Verify your N8N instance URL is accessible
   • Test your N8N API key in a browser or API client
   • Ensure the API key has the correct permissions
3. Verify N8N Login Credentials (if using self-healing)
   • Check X-N8n-Login-Email is set to your n8n account email
   • Check X-N8n-Login-Password is set to your n8n account password
   • These are required for n8n_trigger_execution and self-healing features
   • Make sure the credentials are correct and the account has appropriate permissions
4. Update Configuration
   • Replace credentials in your config file
   • Restart your AI agent after updating

​

Common Causes

• Long-running operations (large workflows, many templates)
• Network instability
• Server timeout settings
• Resource-intensive tool calls

​

Solution

1. Break Down Large Operations
   • Search templates in smaller batches (use limit parameter)
   • Process workflows one at a time instead of bulk operations
   • Use pagination with cursor for large result sets
2. Use Faster Tool Variants
   • Use get_node with detail: "minimal" for quick property checks
   • Use validate_node with mode: "minimal" instead of full validation
   • Use get_template with mode: "nodes_only" for quick previews
3. Increase Timeout Settings
   • Check your MCP client’s timeout configuration
   • Some operations like n8n_trigger_execution may need longer timeouts
4. Restart the Connection
   • Clear npx cache: rm -rf ~/.npm/_npx
   • Restart your AI agent
   • Verify network stability
5. Check Tool Parameters
   • Ensure limit parameters are reasonable (avoid requesting 1000+ items)
   • Use includeExamples: false if you don’t need template examples
   • Disable expensive options like includeTypeInfo unless needed

​

Choose the Right Tool

• Requires N8N login credentials (X-N8n-Login-Email, X-N8n-Login-Password)
• Supports all trigger types: Manual, Chat, Webhook, Form
• AI automatically detects errors and suggests fixes (self-healing)
• Full execution data for debugging

• No login required
• Only works with activated workflows
• Supports: Webhook, Form, Chat triggers

​

Common Solutions

1. Activate Workflow (for n8n_test_workflow)
   Copy

   {
     "id": "workflow-id",
     "operations": [
       {"type": "updateSettings", "settings": {"active": true}}
     ]
   }
   
2. Verify Trigger Configuration
   • Workflow has a valid trigger node
   • Webhook path is correctly configured
   • Chat triggers have a valid chatMessage
3. Debug Failed Executions
   Copy

   // Get error details
   n8n_executions({action: "get", id: "exec-id", mode: "error"})
   
   // Trace multi-workflow chains
   n8n_executions({action: "correlate", executionId: "exec-id"})
   
   // Re-run failed execution
   n8n_executions({action: "retry", id: "exec-id"})
   

​

Why This Happens

• The workflow uses nodes from a newer n8n version
• Community nodes are not installed
• Node packages are missing or outdated

​

Solution

1. Update n8n to Latest Version
   • Check your current version in Settings → About n8n
   • Update to the latest version:
   n8n Cloud: Automatically updated, contact support if issues persist Self-hosted: Follow your hosting provider’s instructions for updating n8n (Docker, npm, etc.)
2. Install Missing Community Nodes
   • Go to Settings → Community nodes
   • Search for and install any missing community nodes
   • Restart n8n after installation
3. Check Node Compatibility
   • Some nodes may be deprecated or renamed in newer versions
   • Use n8n_autofix_workflow to automatically update node types
   • Review the workflow and replace deprecated nodes with current alternatives

​

Solution

rm -rf ~/.npm/_npx

​

Why This Happens

​

Solution by Client

mkdir -p ~/.cursor && touch ~/.cursor/mcp.json

mkdir -p ~/Library/Application\ Support/Claude
touch ~/Library/Application\ Support/Claude/claude_desktop_config.json

​

Solution

1. Check Internet Connection
   • Ensure you have a stable internet connection
   • Try accessing the MCP server URL in a browser
2. Firewall/Proxy Settings
   • Check if your firewall is blocking the connection
   • If using a corporate proxy, ensure npx can access external URLs
   • You may need to configure proxy settings in your environment
3. N8N Instance Accessibility
   • Verify your N8N instance is running and accessible
   • Test the URL in a browser: https://your-instance/api/v1/health
   • Check if the instance requires VPN or special network access