MCP Server Integration

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Overview

The MCP Server integration enables you to use your Relevance AI tools in external AI clients that support the MCP (Model Control Protocol) standard. This powerful feature creates a seamless connection between your Relevance AI workspace and popular AI assistants like Claude and development environments like Cursor.

With MCP Server integration, you maintain a single source of truth for your tools while extending their availability across your entire AI ecosystem. This means the specialized tools you’ve built in Relevance AI can now be accessed and utilized by your favorite AI assistants outside our platform.

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Benefits

• Extended tool availability: Use your Relevance AI tools in Claude, Cursor, and other MCP-compatible AI clients
• Centralized tool management: Update tools in one place and have changes reflect everywhere
• Customizable integration: Select exactly which tools to expose to external clients
• Simple configuration: Generate MCP server settings with just a few clicks
• Seamless workflow integration: Access your specialized tools wherever you work with AI

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How It Works

The MCP Server integration creates a secure bridge between your Relevance AI workspace and external AI clients. When you configure the integration, you select which tools from your workspace you want to make available to external clients. The system then generates the necessary configuration settings that you can copy into your preferred MCP-compatible client.

Once configured, your external AI assistant can access and execute the selected Relevance AI tools as if they were native to that platform. This creates a consistent experience across your entire AI workflow, regardless of which interface you’re using.

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Setting Up MCP Server Integration

Setting up the MCP Server integration is straightforward:

1. Go to your Relevance AI workspace
2. Under “Tools”, navigate to “Export Tools” → “MCP Server”
3. Select the tools you want to share with external clients
4. Click “Generate MCP Server Configuration”
5. Copy your MCP configuration into your preferred client:

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Client-Specific Setup

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Cursor

To use your Relevance AI tools in Cursor:

1. Open Cursor settings
2. Navigate to the MCP tab
3. Click “Add new MCP server”
4. Paste your generated MCP configuration into your mcp.json file
5. Save the configuration

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Claude

To use your Relevance AI tools in Claude:

1. Access Claude’s settings
2. Look for the tool or API integration section
3. Add a new MCP server
4. Paste your generated MCP configuration
5. Save the settings

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Best Practices

• Select tools strategically: Only expose tools that would be useful in external contexts
• Test the integration: After setting up, test each tool to ensure it works as expected
• Update regularly: When you update tools in Relevance AI, regenerate your MCP configuration
• Monitor usage: Keep track of how your tools are being used across different platforms

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Security Considerations

The MCP Server integration maintains the security of your tools while making them accessible to external clients. Authentication is handled through secure tokens, ensuring that only authorized users can access your tools. All communication between Relevance AI and external clients is encrypted to protect your data.

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Troubleshooting

If you encounter issues with the MCP Server integration:

• Verify that your MCP configuration is correctly copied into the external client
• Ensure the external client supports the MCP standard
• Check that the selected tools are compatible with the external client
• Confirm your authentication credentials are valid
• Regenerate the MCP configuration if necessary

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Related Features

Tool Templates - Create powerful tools that can be used both within Relevance AI and through the MCP Server integration.

Create a Tool - Learn how to build custom tools that can be shared across your AI ecosystem.

Customize Tools - Optimize your tools for better performance across different AI clients.

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Conclusion

The MCP Server integration represents a significant step forward in creating a unified AI ecosystem. By allowing your Relevance AI tools to be used in external AI clients, you can maintain consistency across platforms while leveraging the unique strengths of each environment. This integration maximizes your investment in tool development and ensures that your specialized capabilities are available wherever you work with AI.