Qovery

Getting Started

MCP Server Setup

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Overview

The Qovery MCP (Model Context Protocol) Server enables you to use Qovery AI Copilot directly in any MCP-compatible client, including ChatGPT, Claude, and Claude Code. This gives you natural language control over your entire Qovery infrastructure.

Activation Required: Before using the MCP Server, organization administrators must first activate Qovery AI Copilot from the console settings. See the Getting Started guide for activation instructions.

What is MCP? The Model Context Protocol is an open standard developed by Anthropic that allows AI assistants to interact with external tools and systems. Learn more →

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Operating Modes

By default, the MCP Server operates in read-only mode. To enable read-write access, you must explicitly opt in using a URL parameter and have the necessary permissions configured.

• Read-Only Mode (Default)
• Read-Write Mode

Safe exploration - View-only accessIn read-only mode, the Copilot allows you to:

• View information and status
• Get help and recommendations
• Troubleshoot issues
• Monitor deployments
• Analyze infrastructure
• No changes to infrastructure This is the default mode, ensuring safe exploration without risk of accidental modifications.

Permission Hierarchy: The MCP Server is read-only by default. To enable read-write access, you must:

• Add read_write=true to the MCP Server URL
• Have AI write permissions enabled in your organization settings
• Use an API token with sufficient role permissions The most restrictive setting takes precedence. For example, if you add read_write=true but your token has viewer permissions, the Copilot will remain in read-only mode.

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Prerequisites

Before using the MCP Server:

• MCP-Compatible Client: Any MCP-compatible application (tested with ChatGPT, Claude, and Claude Code)
• Qovery Account: Active account with infrastructure
• API Token: Generate from Qovery Console (Settings → API Tokens)

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Setup

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1. Generate Your Qovery API Token

1

Open Qovery Console

Go to console.qovery.com

2

Navigate to Settings

Click on the settings icon in your organization

3

Access API Tokens

Go to API Tokens section

4

Generate Token

Click “Generate Token” and copy it

Save this token securely. You won’t be able to see it again!

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2. Configure Your MCP Client

The Qovery MCP Server is accessible via the following URL:

https://mcp-api-ai.qovery.com/mcp

You can optionally include your API token and operating mode as query parameters:

https://mcp-api-ai.qovery.com/mcp?token=<your-token>

To enable read-write mode (requires appropriate permissions):

https://mcp-api-ai.qovery.com/mcp?token=<your-token>&read_write=true

Token in URL: If you provide the token in the URL, you won’t be prompted for authentication during the session. If omitted, the token will be requested when you first interact with the server.

Operating Mode: By default, the MCP Server operates in read-only mode. To enable read-write access, add read_write=true to the URL. This requires AI write permissions to be enabled in your organization settings and a token with sufficient permissions.

Add the Qovery MCP Server to your MCP client’s configuration using:

Server URL: https://mcp-api-ai.qovery.com/mcp

Refer to your specific MCP client’s documentation for detailed setup instructions on how to add a custom MCP server.

The Qovery MCP Server is also available through the MCP Registry.

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Usage

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Authentication with API Token

The Qovery MCP Server supports 3 authentication methods:

• 1. Query Parameter
• 2. Custom Header
• 3. Authorization Header

Add your token directly to the MCP Server URL:

https://mcp-api-ai.qovery.com/mcp?token=your_qovery_token

To force read-only mode:

https://mcp-api-ai.qovery.com/mcp?token=your_qovery_token&read-only=true

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Usage Examples

Once authenticated, you can interact with your infrastructure naturally:

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Check Status

"Show me all my environments"
"What's the status of production?"
"List applications in the staging environment"

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Deploy Applications

"Deploy the latest version of my-api to production"
"Restart the frontend application"
"Scale the API service to 5 replicas"

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Troubleshoot Issues

"Why is my deployment failing?"
"Show me error logs from the last hour"
"Debug the connection timeout in staging"

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Manage Infrastructure

"Create a new environment called feature-test"
"Clone production to staging"
"Stop all services in the dev environment"

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Troubleshooting

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MCP Server Not Connecting

Issue: Client doesn’t show Qovery tools or cannot connect Solutions:

1. Verify the MCP Server URL is correct: https://mcp-api-ai.qovery.com/mcp
2. Check your internet connection
3. Restart your MCP client
4. Contact Qovery Support if the issue persists

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Authentication Errors

Issue: “Authentication failed” or “Invalid token” errors Solutions:

1. Verify your API token is correct (check for copy-paste errors)
2. Ensure the token hasn’t been revoked or expired
3. Verify the token has the necessary permissions for the requested operation
4. Generate a new API token if needed from Qovery Console

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Token Not Persisting

Issue: Need to re-enter token for each question Solutions:

1. Ensure you’re staying in the same conversation
2. Provide the token at the beginning of new conversations
3. Check if your client is maintaining the conversation context

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Security Best Practices

API Token Security:

• Never share your API tokens publicly
• Don’t commit tokens to version control
• Revoke tokens you no longer need from Qovery Console
• Use tokens with the minimum required permissions
• Rotate tokens regularly

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Token Permissions

The API token has the same permissions as the role you selected during creation:

• Can only access resources within your organization
• Respects organization RBAC policies
• All actions are audited in Qovery Console

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Next Steps

Console Copilot

Use the built-in Console Copilot for quick help

Slack Bot

Set up the Slack Bot for team collaboration

View Capabilities

Explore everything Copilot can do

Common Tasks

Practical examples and use cases

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Resources

• MCP Protocol: modelcontextprotocol.io
• Claude Desktop: claude.ai/download
• Technical Blog: How We Built an Agentic DevOps Copilot

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