ai-ml-api-automation

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AI ML API Automation via Rube MCP

通过Rube MCP实现AI ML API自动化

Automate AI ML API operations through Composio's AI ML API toolkit via Rube MCP.

Toolkit docs: composio.dev/toolkits/ai_ml_api

通过Rube MCP，借助Composio的AI ML API工具包实现AI ML API操作自动化。

工具包文档：composio.dev/toolkits/ai_ml_api

Prerequisites

前提条件

Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
Active AI ML API connection via
```
RUBE_MANAGE_CONNECTIONS
```
with toolkit
```
ai_ml_api
```
Always call
```
RUBE_SEARCH_TOOLS
```
first to get current tool schemas

必须已连接Rube MCP（需启用RUBE_SEARCH_TOOLS）
通过
```
RUBE_MANAGE_CONNECTIONS
```
使用
```
ai_ml_api
```
工具包建立活跃的AI ML API连接
请始终先调用
```
RUBE_SEARCH_TOOLS
```
以获取最新的工具架构

Setup

设置步骤

Get Rube MCP: Add

https://rube.app/mcp

as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

Verify Rube MCP is available by confirming
```
RUBE_SEARCH_TOOLS
```
responds
Call
```
RUBE_MANAGE_CONNECTIONS
```
with toolkit
```
ai_ml_api
```
If connection is not ACTIVE, follow the returned auth link to complete setup
Confirm connection status shows ACTIVE before running any workflows

获取Rube MCP：在客户端配置中添加

https://rube.app/mcp

作为MCP服务器。无需API密钥，只需添加该端点即可使用。

通过确认
```
RUBE_SEARCH_TOOLS
```
能正常响应，验证Rube MCP是否可用
使用
```
ai_ml_api
```
工具包调用
```
RUBE_MANAGE_CONNECTIONS
```
如果连接状态未显示为ACTIVE，请按照返回的授权链接完成设置
在运行任何工作流之前，确认连接状态显示为ACTIVE

Tool Discovery

工具发现

Always discover available tools before executing workflows:

RUBE_SEARCH_TOOLS
queries: [{use_case: "AI ML API operations", known_fields: ""}]
session: {generate_id: true}

This returns available tool slugs, input schemas, recommended execution plans, and known pitfalls.

在执行工作流之前，请始终先发现可用工具：

RUBE_SEARCH_TOOLS
queries: [{use_case: "AI ML API operations", known_fields: ""}]
session: {generate_id: true}

该命令会返回可用的工具别名、输入架构、推荐的执行计划以及已知的注意事项。

Core Workflow Pattern

核心工作流模式

Step 1: Discover Available Tools

步骤1：发现可用工具

RUBE_SEARCH_TOOLS
queries: [{use_case: "your specific AI ML API task"}]
session: {id: "existing_session_id"}

RUBE_SEARCH_TOOLS
queries: [{use_case: "your specific AI ML API task"}]
session: {id: "existing_session_id"}

Step 2: Check Connection

步骤2：检查连接

RUBE_MANAGE_CONNECTIONS
toolkits: ["ai_ml_api"]
session_id: "your_session_id"

RUBE_MANAGE_CONNECTIONS
toolkits: ["ai_ml_api"]
session_id: "your_session_id"

Step 3: Execute Tools

步骤3：执行工具

RUBE_MULTI_EXECUTE_TOOL
tools: [{
  tool_slug: "TOOL_SLUG_FROM_SEARCH",
  arguments: {/* schema-compliant args from search results */}
}]
memory: {}
session_id: "your_session_id"

RUBE_MULTI_EXECUTE_TOOL
tools: [{
  tool_slug: "TOOL_SLUG_FROM_SEARCH",
  arguments: {/* schema-compliant args from search results */}
}]
memory: {}
session_id: "your_session_id"

Known Pitfalls

已知注意事项

Always search first: Tool schemas change. Never hardcode tool slugs or arguments without calling
```
RUBE_SEARCH_TOOLS
```
Check connection: Verify
```
RUBE_MANAGE_CONNECTIONS
```
shows ACTIVE status before executing tools
Schema compliance: Use exact field names and types from the search results
Memory parameter: Always include
```
memory
```
in
```
RUBE_MULTI_EXECUTE_TOOL
```
calls, even if empty (
```
{}
```
)
Session reuse: Reuse session IDs within a workflow. Generate new ones for new workflows
Pagination: Check responses for pagination tokens and continue fetching until complete

始终先搜索：工具架构会发生变化。请勿在未调用
```
RUBE_SEARCH_TOOLS
```
的情况下硬编码工具别名或参数
检查连接：在执行工具之前，确认
```
RUBE_MANAGE_CONNECTIONS
```
显示的状态为ACTIVE
架构合规：使用搜索结果中给出的精确字段名称和类型
Memory参数：在调用
```
RUBE_MULTI_EXECUTE_TOOL
```
时请始终包含
```
memory
```
参数，即使它是空的（
```
{}
```
）
会话复用：在同一个工作流中复用会话ID。针对新的工作流生成新的会话ID
分页处理：检查响应中的分页令牌，并持续获取数据直到完成

Quick Reference

快速参考

Operation	Approach
Find tools	`RUBE_SEARCH_TOOLS` with AI ML API-specific use case
Connect	`RUBE_MANAGE_CONNECTIONS` with toolkit `ai_ml_api`
Execute	`RUBE_MULTI_EXECUTE_TOOL` with discovered tool slugs
Bulk ops	`RUBE_REMOTE_WORKBENCH` with `run_composio_tool()`
Full schema	`RUBE_GET_TOOL_SCHEMAS` for tools with `schemaRef`

Powered by Composio

操作	方法
查找工具	使用针对AI ML API的特定用例调用 `RUBE_SEARCH_TOOLS`
建立连接	使用 `ai_ml_api` 工具包调用 `RUBE_MANAGE_CONNECTIONS`
执行	使用发现的工具别名调用 `RUBE_MULTI_EXECUTE_TOOL`
批量操作	在 `RUBE_REMOTE_WORKBENCH` 中使用 `run_composio_tool()`
完整架构	为带有 `schemaRef` 的工具调用 `RUBE_GET_TOOL_SCHEMAS`

由Composio提供支持