Make MCP Server
建立 MCP 服务器
模型上下文协议服务器,使 Make 场景能够被 AI 助手用作工具。此集成允许 AI 系统触发您的 Make 自动化工作流程并与其交互。
工作原理
MCP 服务器:
连接到您的 Make 帐户并识别所有配置了“按需”调度的场景
解析并解决每个场景的输入参数,为AI助手提供有意义的参数描述
允许人工智能助手调用具有适当参数的场景
以结构化 JSON 形式返回场景输出(目前处于封闭测试阶段),使 AI 助手能够正确解释结果
Related MCP server: Automatisch MCP Server
好处
将您的 Make 场景转化为可供 AI 助手调用的工具
在 Make 中维护复杂的自动化逻辑,同时向 AI 系统公开功能
在您的人工智能助手和现有自动化工作流程之间建立双向通信
与 Claude Desktop 一起使用
先决条件
NodeJS
MCP 客户端(如 Claude 桌面应用程序)
使用
scenarios:read和scenarios:run范围创建 API 密钥
安装
要将此服务器与 Claude Desktop 应用程序一起使用,请将以下配置添加到claude_desktop_config.json的“mcpServers”部分:
{
"mcpServers": {
"make": {
"command": "npx",
"args": ["-y", "@makehq/mcp-server"],
"env": {
"MAKE_API_KEY": "<your-api-key>",
"MAKE_ZONE": "<your-zone>",
"MAKE_TEAM": "<your-team-id>"
}
}
}
}MAKE_API_KEY- 您可以在 Make 配置文件中生成 API 密钥。MAKE_ZONE- 您的组织所在的区域(例如,eu2.make.com)。MAKE_TEAM- 您可以在团队页面的 URL 中找到该 ID。
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseBqualityDmaintenanceEnables Claude Desktop to trigger and interact with Make.com automation scenarios through webhooks. Allows users to execute complex workflows and integrations with third-party services like Google Sheets, Notion, and Slack using natural language commands.3147MIT
- AlicenseBqualityDmaintenanceEnables AI assistants to interact with Automatisch workflow automation platform, allowing them to create, manage, and monitor workflows, connections, and executions through natural language commands.10137MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to trigger and interact with Make automation workflows by exposing on-demand scenarios as callable tools. Allows AI systems to invoke Make scenarios with parameters and receive structured JSON responses.97MIT
- AlicenseNot gradedqualityDmaintenanceThis server enables AI assistants to discover, parameterize, and trigger Make.com automation workflows configured for on-demand execution. It allows users to execute scenarios and receive structured JSON results, bridging the gap between AI assistants and complex automation ecosystems.97MIT
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