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mcp-scaleway-functions

@cyclimse/mcp-scaleway-functions
0 Stars 2 次浏览 cyclimse 更新于 2026-08-23

Unofficial MCP Server for Scaleway Serverless Functions

MCP 服务配置

复制以下 JSON 到 OPClaw 或其他 MCP 客户端的配置文件中即可使用

{
  "mcpServers": {
    "docker.io/cyclimse/mcp-scaleway-functions": {
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/cyclimse/mcp-scaleway-functions:0.3.3"
      ],
      "command": "docker"
    }
  }
}

可用工具 (5 个)

该服务在 MCP 协议中暴露的工具,AI 可按需调用

tavily_search 14 个参数 需填 1 项

Search the web for current information on any topic. Use for news, facts, or data beyond your knowledge cutoff. Returns snippets and source URLs.

必填参数:query

tavily_extract 6 个参数 需填 1 项

Extract content from URLs. Returns raw page content in markdown or text format.

必填参数:urls

tavily_crawl 11 个参数 需填 1 项

Crawl a website starting from a URL. Extracts content from pages with configurable depth and breadth.

必填参数:url

tavily_map 8 个参数 需填 1 项

Map a website's structure. Returns a list of URLs found starting from the base URL.

必填参数:url

tavily_research 2 个参数 需填 1 项

Perform comprehensive research on a given topic or question. Use this tool when you need to gather information from multiple sources to answer a question or complete a task. Returns a detailed response based on the research findings.

必填参数:input

服务介绍

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

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