DataWorks logo

DataWorks

Organization
aliyun

A Model Context Protocol (MCP) server that provides tools for AI, allowing it to interact with the DataWorks Open API through a standardized interface. This implementation is based on the Aliyun Open API and enables AI agents to perform cloud resources operations seamlessly.

Publisheraliyun
Repositoryalibabacloud-dataworks-mcp-server
LanguageTypeScript
Forks
16
Stars
51
Available tools
186
Transport typestdio
Categories
LicenseApache-2.0
Links
  • Connect tools to AI workflows

    DataWorks exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 186 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    51 stars and 16 forks from the linked repository.

MseeP.ai Security Assessment Badge

Try DataWorks Agent

Want a ready-to-use AI experience for DataWorks without manual MCP setup?

DataWorks Agent is Alibaba Cloud's built-in intelligent assistant for data development and operations. It connects to your DataWorks workspace out of the box, so you can use natural language to explore metadata, develop nodes, troubleshoot tasks, and manage resources—no local MCP server configuration required.

DataWorks AgentThis MCP Server
Best forQuick start in the DataWorks consoleCustom AI clients (Cursor, Cline, etc.)
SetupOpen and use in browserInstall, configure AK, and connect MCP
IntegrationNative DataWorks experienceOpen API via MCP protocol

👉 Get started: https://dataworks.data.alibabacloud.com/product/agent?source=github

DataWorks MCP Server

A Model Context Protocol (MCP) server that provides tools for AI, allowing it to interact with the DataWorks Open API through a standardized interface. This implementation is based on the Aliyun Open API and enables AI agents to perform cloud resources operations seamlessly.

If you prefer embedding DataWorks capabilities into your own AI workflow or IDE, follow the installation guide below.

Overview

This MCP server:

  • Interact with DataWorks Open API
  • Manage DataWorks resources

The server implements the Model Context Protocol specification to standardize cloud resource interactions for AI agents.

Prerequisites

  • Node.js (v16 or higher)
  • pnpm (recommended), npm, or yarn
  • DataWorks Open API with access key and secret key

Installation

Option 1: Install from npm (recommend for clients like Cursor/Cline)

bash
# Install globally
npm install -g alibabacloud-dataworks-mcp-server

# Or install locally in your project
npm install alibabacloud-dataworks-mcp-server

Option 2: Build from Source (for developers)

  1. Clone this repository:
bash
git clone https://github.com/aliyun/alibabacloud-dataworks-mcp-server
cd alibabacloud-dataworks-mcp-server
  1. Install dependencies (pnpm is recommended, npm is supported):
bash
pnpm install
  1. Build the project:
bash
pnpm run build
  1. Development the project (by @modelcontextprotocol/inspector):
bash
pnpm run dev

open http://localhost:5173

Configuration

MCP Server Configuration

If you installed via npm (Option 1):

json
{
  "mcpServers": {
    "alibabacloud-dataworks-mcp-server": {
      "command": "npx",
      "args": ["alibabacloud-dataworks-mcp-server"],
      "env": {
        "REGION": "your_dataworks_open_api_region_id_here",
        "ALIBABA_CLOUD_ACCESS_KEY_ID": "your_alibaba_cloud_access_key_id",
        "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "your_alibaba_cloud_access_key_secret",
        "TOOL_CATEGORIES": "optional_your_tool_categories_here_ex_UTILS",
        "TOOL_NAMES": "optional_your_tool_names_here_ex_ListProjects"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

If you built from source (Option 2):

json
{
  "mcpServers": {
    "alibabacloud-dataworks-mcp-server": {
      "command": "node",
      "args": ["/path/to/alibabacloud-dataworks-mcp-server/build/index.js"],
      "env": {
        "REGION": "your_dataworks_open_api_region_id_here",
        "ALIBABA_CLOUD_ACCESS_KEY_ID": "your_alibaba_cloud_access_key_id",
        "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "your_alibaba_cloud_access_key_secret",
        "TOOL_CATEGORIES": "optional_your_tool_categories_here_ex_SERVER_IDE_DEFAULT",
        "TOOL_NAMES": "optional_your_tool_names_here_ex_ListProjects"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Environment Setup

init variables in your environment:

env
# DataWorks Configuration
REGION=your_dataworks_open_api_region_id_here
ALIBABA_CLOUD_ACCESS_KEY_ID=your_alibaba_cloud_access_key_id
ALIBABA_CLOUD_ACCESS_KEY_SECRET=your_alibaba_cloud_access_key_secret
TOOL_CATEGORIES=optional_your_tool_categories_here_ex_SERVER_IDE_DEFAULT
TOOL_NAMES=optional_your_tool_names_here_ex_ListProjects

Configuration Description

  • Use Guide Description Link

Project Structure

alibabacloud-dataworks-mcp-server/
├── src/
│   ├── index.ts          # Main entry point
├── package.json
└── tsconfig.json

Available Tools

The MCP server provides the following DataWorks tools:

See this link

Security Considerations

  • Keep your private key secure and never share it
  • Use environment variables for sensitive information
  • Regularly monitor and audit AI agent activities

Troubleshooting

If you encounter issues:

  1. Verify your Aliyun Open API access key and secret key are correct
  2. Check your region id is correct
  3. Ensure you're on the intended network (mainnet, testnet, or devnet)
  4. Verify the build was successful

Dependencies

Key dependencies include:

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the Apache 2.0 License.

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "alibabacloud-dataworks-mcp-server": {
      "command": "npx",
      "args": [
        "alibabacloud-dataworks-mcp-server"
      ],
      "env": {
        "REGION": "your_dataworks_open_api_region_id_here",
        "ALIBABA_CLOUD_ACCESS_KEY_ID": "your_alibaba_cloud_access_key_id",
        "ALIBABA_CLOUD_ACCESS_KEY_SECRET": "your_alibaba_cloud_access_key_secret",
        "TOOL_CATEGORIES": "optional_your_tool_categories_here_ex_UTILS",
        "TOOL_NAMES": "optional_your_tool_names_here_ex_ListProjects"
      }
    }
  }
}

Available Tools

  • ListWorkflows

    获取工作流列表

  • UpdateMetaCollection

    更新数据地图集合对象

  • CreateResource

    创建数据开发文件资源

  • ResumeTaskInstances

    恢复任务实例

  • GetProjectMember

    查询工作空间成员详情

  • UpdateAlertRule

    更新自定义监控告警规则 *This Tool has a 'MCP Resource',please request UpdateAlertRule(MCP Resource) to get more examples for using this tool.

  • UpdateNode

    更新数据开发节点信息

  • CreateDataQualityRule

    创建质量规则 *This Tool has a 'MCP Resource',please request CreateDataQualityRule(MCP Resource) to get more examples for using this tool.

  • GetTaskInstance

    获取任务实例的详情

  • RevokeTablePermission

    撤销用户的表权限

  • ListPermissionApplyOrders

    查询权限申请单列表

  • GetResource

    获取数据开发文件资源详情

  • GetCreateWorkflowInstancesResult

    获取创建工作流实例结果

  • GetColumn

    获取数据地图数据表字段信息

  • GetNetwork

    获取某个网络资源详细信息

  • ListColumns

    查询数据地图数据表字段列表

  • GetDataQualityRule

    查询质量规则详情

  • RenameWorkflowDefinition

    重命名数据开发工作流

  • DeleteWorkflow

    删除工作流

  • DeleteDIAlarmRule

    删除数据集成同步任务告警规则

  • DeleteMetaCollection

    删除数据地图集合对象

  • ListLineages

    查询数据地图实体血缘列表

  • UpdateColumnBusinessMetadata

    更新数据地图数据表字段的业务元数据

  • SuspendTaskInstances

    暂停任务实例

  • GetTopic

    获取事件的详情

  • UpdateWorkflowDefinition

    更新数据开发工作流信息

  • MoveFunction

    移动数据开发函数路径

  • ListProjectRoles

    获取工作空间角色详情列表

  • GetDatabase

    获取数据地图数据库详情

  • DeleteDataQualityRule

    删除质量规则

  • UpdateResource

    更新数据开发文件资源信息

  • ListTables

    查询数据地图数据表列表

  • ListDataQualityEvaluationTasks

    查询质量监控任务列表

  • ApprovePermissionApplyOrder

    审批权限申请单

  • DeleteFunction

    删除数据开发函数

  • AttachDataQualityRulesToEvaluationTask

    关联数据质量规则与数据质量监控

  • CreateAlertRule

    创建自定义监控告警规则 *This Tool has a 'MCP Resource',please request CreateAlertRule(MCP Resource) to get more examples for using this tool.

  • DeleteDataQualityEvaluationTask

    删除数据质量监控

  • GetRoute

    根据ID获取指定路由信息

  • UpdateTaskInstances

    修改任务实例属性

  • DeleteDataSource

    删除数据源

  • GetDIJob

    查看数据集成同步任务配置详情

  • ListPipelineRuns

    获取发布流程列表

  • GetDataQualityEvaluationTaskInstance

    获取数据质量校验任务实例详情

  • ListDataServiceApis

    获取数据服务API开发中的信息列表

  • CreateDataQualityEvaluationTask

    创建数据质量监控 *This Tool has a 'MCP Resource',please request CreateDataQualityEvaluationTask(MCP Resource) to get more examples for using this tool.

  • RemoveTaskInstanceDependencies

    移除任务实例的依赖关系

  • GetResourceGroup

    根据ID获取指定资源组信息

  • GetLineageRelationship

    获取数据地图血缘关系

  • MoveResource

    移动数据开发文件资源路径

  • ListNetworks

    获取资源组网络资源列表

  • UpdateTask

    更新任务 *This Tool has a 'MCP Resource',please request UpdateTask(MCP Resource) to get more examples for using this tool.

  • GetPipelineRun

    获取发布流程详细信息

  • GetDataServiceApi

    查询数据服务API开发态的详情

  • ListCatalogs

    查询数据地图数据目录列表

  • GrantMemberProjectRoles

    授予工作空间成员新的空间角色

  • GetDataSource

    查看数据源详情

  • ListProjectMembers

    查询工作空间成员列表

  • GetProject

    获取工作空间详情

  • GetProjectRole

    获取工作空间角色详情

  • DeleteProjectMember

    移除工作空间成员

  • StopTaskInstances

    终止任务实例

  • UpdateDataQualityEvaluationTask

    更新数据质量监控 *This Tool has a 'MCP Resource',please request UpdateDataQualityEvaluationTask(MCP Resource) to get more examples for using this tool.

  • ListWorkflowInstances

    获取工作流实例列表

  • CreateNode

    创建数据开发节点 *This Tool has a 'MCP Resource',please request CreateNode(MCP Resource) to get more examples for using this tool.

  • CreateDIJob

    创建数据集成同步任务 *This Tool has a 'MCP Resource',please request CreateDIJob(MCP Resource) to get more examples for using this tool.

  • ListTaskInstances

    获取任务实例列表

  • GetDIJobLog

    查看数据集成同步任务的运行日志

  • GetSchema

    获取数据地图数据库模式信息

  • ListTaskOperationLogs

    获取任务的操作日志列表

  • ListDataSources

    获取数据源列表

  • GetNode

    获取数据开发节点详情

  • GetDataServiceApiTest

    获取API测试结果

  • GetTask

    获取任务的详情

  • CreatePermissionApplyOrder

    创建权限申请单 *This Tool has a 'MCP Resource',please request CreatePermissionApplyOrder(MCP Resource) to get more examples for using this tool.

  • ListDIJobs

    获取数据集成同步任务配置列表

  • TestDataServiceApi

    测试数据服务API

  • ListDatabases

    查询数据地图数据库列表

  • ListCrawlerTypes

    获取数据地图元数据采集器类型列表

  • GetMetaCollection

    获取数据地图集合信息

  • ImportWorkflowDefinition

    导入数据开发工作流

  • TriggerSchedulerTaskInstance

    触发调度任务实例

  • UpdateDataServiceApi

    更新数据服务API开发态的信息

  • CreateDataQualityEvaluationTaskInstance

    创建数据质量校验监控实例

  • StopDIJob

    停止数据集成同步任务

  • StopWorkflowInstances

    终止工作流实例

  • DeleteNode

    删除数据开发节点

  • GetWorkflowDefinition

    获取数据开发工作流详情

  • DeleteResource

    删除数据开发文件资源

  • GetFunction

    获取数据开发函数详情

  • ListDataAssetTags

    查询标签列表

  • UpdateFunction

    更新数据开发函数信息

  • CreateWorkflowDefinition

    创建数据开发工作流

  • ListDataQualityResults

    查询质量结果列表

  • StartDIJob

    启动数据集成同步任务

  • ListTasks

    获取任务列表

  • CreateDIAlarmRule

    创建数据集成同步任务告警规则 *This Tool has a 'MCP Resource',please request CreateDIAlarmRule(MCP Resource) to get more examples for using this tool.

  • GetDataQualityEvaluationTask

    查询数据质量监控详情

  • ListResources

    获取数据开发文件资源列表

  • TestDataSourceConnectivity

    测试数据源的连通性

  • CreateWorkflowInstances

    创建工作流实例 *This Tool has a 'MCP Resource',please request CreateWorkflowInstances(MCP Resource) to get more examples for using this tool.

  • UpdateWorkflow

    更新工作流 *This Tool has a 'MCP Resource',please request UpdateWorkflow(MCP Resource) to get more examples for using this tool.

  • GetWorkflow

    获取工作流的详情

  • ListDIJobRunDetails

    获取数据集成同步任务运行的执行进展

  • RerunTaskInstances

    重跑任务实例

  • CreateProjectMember

    创建工作空间成员

  • AbolishDataServiceApi

    下线数据服务API

  • SaveDataServiceApiTestResult

    保存API测试结果

  • ListDataQualityRules

    查询质量规则列表

  • GetAlertRule

    获取自定义监控告警规则

  • ListAlertMessages

    获取报警信息的列表

  • ListUpstreamTaskInstances

    获取上游任务实例列表

  • UpdateDataQualityRule

    更新质量规则

  • UpdateTableBusinessMetadata

    更新数据地图数据表的业务元数据

  • CreateFunction

    创建数据开发函数

  • CreateLineageRelationship

    注册数据地图血缘关系

  • GetTaskInstanceLog

    获取任务实例的运行日志

  • RemoveEntityFromMetaCollection

    从数据地图集合中移除实体对象

  • ListDIJobEvents

    获取数据集成同步任务的运行事件列表

  • GetCatalog

    获取数据地图数据目录详情

  • ListWorkflowDefinitions

    获取数据开发工作流列表

  • RenameNode

    重命名数据开发节点

  • CreateDataServiceApi

    创建数据服务API

  • ListAlertRules

    获取自定义规则列表

  • ListTopics

    获取或搜索事件列表

  • ListDIJobMetrics

    查看数据集成同步任务运行指标

  • PublishDataServiceApi

    发布数据服务API

  • DeleteAlertRule

    删除自定义规则

  • DeleteDataServiceApi

    删除数据服务API

  • ListEntitiesInMetaCollection

    查询数据地图集合中的实体列表

  • ListSchemas

    查询数据地图数据库模式列表

  • ListNodeDependencies

    获取数据开发节点的依赖节点

  • BatchUpdateTasks

    批量更新任务 *This Tool has a 'MCP Resource',please request BatchUpdateTasks(MCP Resource) to get more examples for using this tool.

  • SubmitDataServiceApi

    提交数据服务API

  • ListFunctions

    获取数据开发函数列表

  • GetAlertMessage

    查询报警信息

  • DeleteTask

    删除任务

  • GetTable

    获取数据地图数据表详情

  • DeleteDIJob

    删除数据集成同步任务

  • ListMetaCollections

    查询数据地图集合列表

  • ListDataQualityEvaluationTaskInstances

    查询质量监控任务实例列表

  • ListDataSourceSharedRules

    查询数据源分享规则列表

  • RevokeMemberProjectRoles

    撤销空间成员的空间角色

  • StartWorkflowInstances

    启动工作流实例

  • ListDataQualityRuleTemplates

    查询质量规则模版列表

  • CreateDISyncTask

    创建数据集成同步任务

  • RenameResource

    重命名数据开发文件资源

  • ListUpstreamTasks

    获取上游任务列表

  • DeleteLineageRelationship

    删除数据地图血缘关系

  • GetPermissionApplyOrderDetail

    查询权限申请单的详细信息

  • ListTaskInstanceOperationLogs

    获取任务实例的操作日志列表

  • SetSuccessTaskInstances

    置成功任务实例

  • AddEntityIntoMetaCollection

    向数据地图集合中添加实体对象

  • CreateMetaCollection

    创建数据地图集合对象

  • UpdateDataSource

    修改数据源

  • GetWorkflowInstance

    获取工作流实例的详情

  • ListResourceGroups

    获取资源组列表

  • UpdateDIJob

    更新数据集成同步任务 *This Tool has a 'MCP Resource',please request UpdateDIJob(MCP Resource) to get more examples for using this tool.

  • ExecuteAdhocWorkflowInstance

    执行临时工作流实例 *This Tool has a 'MCP Resource',please request ExecuteAdhocWorkflowInstance(MCP Resource) to get more examples for using this tool.

  • MoveNode

    移动数据开发节点路径

  • GetTopicInfluence

    获取事件影响的基线实例列表

  • ListDownstreamTaskInstances

    获取下游任务实例列表

  • GetDataServicePublishedApi

    查询数据服务API的发布态信息

  • ListDIAlarmRules

    获取数据集成同步任务告警规则列表

  • ListDownstreamTasks

    获取下游任务列表

  • DeleteWorkflowDefinition

    删除数据开发工作流

  • CloneDataSource

    克隆数据源

  • GetJobStatus

    获取异步API运行状态

  • RenameFunction

    重命名数据开发函数

  • MoveWorkflowDefinition

    移动数据开发工作流路径

  • GetPartition

    获取数据地图数据表的分区详情

  • UpdateDIAlarmRule

    更新数据集成同步任务告警规则 *This Tool has a 'MCP Resource',please request UpdateDIAlarmRule(MCP Resource) to get more examples for using this tool.

  • GetDataQualityRuleTemplate

    查询质量规则模版详情

  • GetRemind

    获取自定义监控报警规则详情

  • ListRoutes

    获取网络资源的路由列表

  • CreateDataSource

    创建数据源

  • ListLineageRelationships

    查询数据地图血缘关系列表

  • ListProjects

    获取工作空间详情列表

  • ListNodes

    获取数据开发节点列表

  • ListDataServicePublishedApis

    获取数据服务API的发布态信息列表

  • ListPartitions

    查询数据地图数据表的分区列表

  • ExecPipelineRunStage

    执行发布流程的指定阶段

  • AbolishPipelineRun

    终止发布流程

  • CreatePipelineRun

    创建发布流程

  • ConvertTimestamps

    将时间戳转成日期或时间。返回内容如果有时间戳,透过此Tool显示成为日期或时间。

  • ToTimestamps

    将日期或时间转成时间戳。

Use DataWorks MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once DataWorks is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add DataWorks as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the DataWorks MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "dataworks": {
      "command": "npx",
      "args": [
        "-y",
        "alibabacloud-dataworks-mcp-server"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the DataWorks MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the DataWorks MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use DataWorks to help me with this task?
DataWorks
Sure. I read it.
Here is what I found using DataWorks.

Frequently asked questions

What is the DataWorks MCP server used for?

DataWorks is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use DataWorks MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use DataWorks with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use DataWorks MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With DataWorks connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect DataWorks MCP to TypingMind?

DataWorks runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does DataWorks MCP provide in TypingMind?

DataWorks exposes 186 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use DataWorks MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If DataWorks requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

UpdateAlertRule

UpdateAlertRule的定义详情,如接口返回范例描述,输入参数范例等

CreateDataQualityRule

CreateDataQualityRule的定义详情,如接口返回范例描述,输入参数范例等

CreateAlertRule

CreateAlertRule的定义详情,如接口返回范例描述,输入参数范例等

CreateDataQualityEvaluationTask

CreateDataQualityEvaluationTask的定义详情,如接口返回范例描述,输入参数范例等

UpdateTask

UpdateTask的定义详情,如接口返回范例描述,输入参数范例等

UpdateDataQualityEvaluationTask

UpdateDataQualityEvaluationTask的定义详情,如接口返回范例描述,输入参数范例等

CreateNode

CreateNode的定义详情,如接口返回范例描述,输入参数范例等

CreateDIJob

CreateDIJob的定义详情,如接口返回范例描述,输入参数范例等

CreatePermissionApplyOrder

CreatePermissionApplyOrder的定义详情,如接口返回范例描述,输入参数范例等

CreateDIAlarmRule

CreateDIAlarmRule的定义详情,如接口返回范例描述,输入参数范例等

CreateWorkflowInstances

CreateWorkflowInstances的定义详情,如接口返回范例描述,输入参数范例等

UpdateWorkflow

UpdateWorkflow的定义详情,如接口返回范例描述,输入参数范例等

BatchUpdateTasks

BatchUpdateTasks的定义详情,如接口返回范例描述,输入参数范例等

UpdateDIJob

UpdateDIJob的定义详情,如接口返回范例描述,输入参数范例等

ExecuteAdhocWorkflowInstance

ExecuteAdhocWorkflowInstance的定义详情,如接口返回范例描述,输入参数范例等

UpdateDIAlarmRule

UpdateDIAlarmRule的定义详情,如接口返回范例描述,输入参数范例等

Related MCP Servers

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇