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MCP Scaleway Functions

Unofficial MCP Server for Scaleway Serverless Functions

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Scored 5 months ago · breakdown

About MCP Scaleway Functions

MCP Scaleway Functions is an MCP server in the Cloud category: unofficial MCP Server for Scaleway Serverless Functions. It has been installed 0 times through Conduid.

Install

Clone
git clone https://github.com/cyclimse/mcp-scaleway-functions

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

MCP Scaleway Functions

Model Context Protocol (MCP) server to manage and deploy Scaleway Serverless Functions using the Model Context Protocol standard.

[!CAUTION] This project is unofficial and not affiliated with or endorsed by Scaleway. Some small safety measures are in place to prevent the LLM from doing destructive actions, but they're not foolproof. Use at your own risk.

Getting Started

Download the latest release from the releases page or build it from source using Go.

Run the MCP server:

./mcp-scaleway-functions

By default, the MCP server runs with the SSE transport on http://localhost:8080, but you can also change it to use Standard I/O (stdio) transport via the --transport stdio flag.

Then, configure your IDE or tool of choice to connect to the MCP server. Here are some examples:

VSCode (sse example)

Add a new server configuration in your .vscode/mcp.json file:

{
	"servers": {
		"mcp-scaleway-functions": {
			"url": "http://localhost:8080",
			"type": "http",
		}
	},
}

Crush (stdio example)

Crush is an open-source coding agent that supports MCP. You can find more information about in the Crush repository.

Add a new server configuration in your ~/.config/crush/crush.json file:

{
  "$schema": "https://charm.land/crush.json",
  "mcp": {
    "scaleway-functions": {
      "type": "stdio",
      "command": "mcp-scaleway-functions",
      "args": ["--transport", "stdio"],
      "timeout": 600,
      "disabled": false
    }
  }
}

You can even use Crush with Scaleway Generative APIs by adding a new provider in the same ~/.config/crush/crush.json file:

{
  "mcp": {
	// ... see above ...
  },
  "providers": {
    "scaleway": {
      "name": "Scaleway",
      "base_url": "https://api.scaleway.ai/v1/",
      "type": "openai",
	  // To fetch from environment variables, use the `$VAR_NAME` syntax.
	  // Note: this key requires the "GenerativeApisModelAccess" permission.
      "api_key": "$SCW_SECRET_KEY",
      "models": [
        {
          "name": "Qwen coder",
          "id": "qwen3-coder-30b-a3b-instruct",
          "context_window": 128000,
          "default_max_tokens": 8000
        }
      ]
    }
  }
}

That's it 🎉! Have fun vibecoding and vibedevoopsing as you please.

Configuration

By default, the MCP server reads from the standard Scaleway configuration file located at ~/.config/scw/config.yaml.

Further configuration can be done via the Scaleway environment variables to configure the MCP server.

For instance, you can set a region to work in via the SCW_DEFAULT_REGION environment variable.

SCW_DEFAULT_REGION=nl-ams ./mcp-scaleway-functions

Available Tools

Tool Description
create_and_deploy_function_namespace Create and deploy a new function namespace.
list_function_namespaces List all function namespaces.
delete_function_namespace Delete a function namespace.
list_functions List all functions in a namespace.
list_function_runtimes List all available function runtimes.
create_and_deploy_function Create and deploy a new function.
update_function Update the code or the configuration of an existing function.
delete_function Delete a function.
download_function Download the code of a function. This is useful to work on an existing function.
fetch_function_logs Fetch the logs of a function.
add_dependency Add a dependency to a local function. Useful for dependencies that rely on native code and therefore need Docker to be installed.

Debugging

You can enable debug logging by using the --debug flag when starting the MCP server. This will log all requests and responses to/from the Scaleway API.

To configure the log level, use the --log-level flag (default is info). Available log levels are: debug, info, warn, error.

Logs are stored in the $XDG_STATE_HOME/mcp-scaleway-functions directory (usually ~/.local/state/mcp-scaleway-functions).

Development

Running tests:

go tool gotestsum --format testdox

Generating mocks:

go tool mockery

README mirrored from the source repository 5 months ago. The original is authoritative.

Questions

About MCP Scaleway Functions

How do I install MCP Scaleway Functions?

Run git clone https://github.com/cyclimse/mcp-scaleway-functions, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is MCP Scaleway Functions safe to use with an AI agent?

Its trust score is 34 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is MCP Scaleway Functions still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.