Scaleway MCP Server
Expose Scaleway cloud elements, audit bare metal nodes, and manage S3-compatible objects.
Quick Answer / TL;DR
The Scaleway MCP server establishes a secure, local or remote JSON-RPC 2.0 communication tunnel, allowing AI models (like Claude or Cursor) to automatically discover and execute capabilities (tools, prompts, and resources) within the Scaleway ecosystem with extremely low latency.
Key Takeaways
- Monitor bare metal capacities
- Manage file storage parameters
- Track network balance
Core Integration Concept
Connecting the model to Scaleway bypasses complex setup. The LLM can auto-discover what endpoints are active, what input variables are expected, and how answers will be delivered.
Verified Use Cases
Setup Overview
Connection Setup Checklist
- Prepare Credentials: Obtain your Scaleway Token credentials directly from your Scaleway settings.
- Update Config: Add the executable tool command structure directly to your Claude config file.
- Restart & Confirm: Reload the desktop model client to complete the connection handshake sequence.
Sample Connection Schema
{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "execute_scaleway",
"arguments": {
"query": "status_check"
}
},
"id": 1
}Security Considerations
To guarantee perfect data isolation, safeguard the Scaleway Token credentials. Always run integrations in sandboxed contexts to block unsolicited access.
Best Practices
- Configure exact resource boundaries for the Bare metal telemetry feature.
- Configure exact resource boundaries for the Bucket actions feature.
- Configure exact resource boundaries for the Load balancer metrics feature.
- Configure exact resource boundaries for the Cost diagnostics feature.
Required Auth Keys
Scaleway Token
Deploy Scaleway Server
Deploy this Scaleway integration to our global edge container cluster. Zero DevOps, instant SSE.
Related Connectors
Scaleway - FAQ
Contextual information and technical support details regarding Model Context Protocol integration