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flowiseai-automation skill

/flowiseai-automation

This skill automates Flowiseai tasks via Rube MCP by discovering current tool schemas first to ensure accurate execution and connection status.

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---
name: flowiseai-automation
description: "Automate Flowiseai tasks via Rube MCP (Composio). Always search tools first for current schemas."
requires:
  mcp: [rube]
---

# Flowiseai Automation via Rube MCP

Automate Flowiseai operations through Composio's Flowiseai toolkit via Rube MCP.

**Toolkit docs**: [composio.dev/toolkits/flowiseai](https://composio.dev/toolkits/flowiseai)

## Prerequisites

- Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
- Active Flowiseai connection via `RUBE_MANAGE_CONNECTIONS` with toolkit `flowiseai`
- Always call `RUBE_SEARCH_TOOLS` first to get current tool schemas

## Setup

**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.

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

## Tool Discovery

Always discover available tools before executing workflows:

```
RUBE_SEARCH_TOOLS
queries: [{use_case: "Flowiseai operations", known_fields: ""}]
session: {generate_id: true}
```

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

## Core Workflow Pattern

### Step 1: Discover Available Tools

```
RUBE_SEARCH_TOOLS
queries: [{use_case: "your specific Flowiseai task"}]
session: {id: "existing_session_id"}
```

### Step 2: Check Connection

```
RUBE_MANAGE_CONNECTIONS
toolkits: ["flowiseai"]
session_id: "your_session_id"
```

### Step 3: Execute Tools

```
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

- **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

## Quick Reference

| Operation | Approach |
|-----------|----------|
| Find tools | `RUBE_SEARCH_TOOLS` with Flowiseai-specific use case |
| Connect | `RUBE_MANAGE_CONNECTIONS` with toolkit `flowiseai` |
| 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](https://composio.dev)*

Overview

This skill automates Flowiseai tasks by orchestrating Composio’s Flowiseai toolkit through a Rube MCP connection. It provides a repeatable pattern to discover tools, validate connections, and execute operations safely. The emphasis is on always searching tools first to get current schemas and on strict schema compliance to avoid runtime errors.

How this skill works

The skill uses RUBE_SEARCH_TOOLS to discover available Flowiseai tools and their input schemas, then verifies an active Flowiseai connection with RUBE_MANAGE_CONNECTIONS. After discovery and validation, it runs one or more tools via RUBE_MULTI_EXECUTE_TOOL (including a memory object) or uses RUBE_REMOTE_WORKBENCH for bulk operations. It supports session reuse and pagination handling for robust workflows.

When to use it

  • Automating Flowiseai workflows that require dynamic tool discovery
  • Running multi-step or bulk Flowiseai operations reliably
  • Integrating Flowiseai tooling into larger agent pipelines or CI jobs
  • When tool schemas may change frequently and must be fetched at runtime
  • When you need to manage and verify Flowiseai connections programmatically

Best practices

  • Always call RUBE_SEARCH_TOOLS first; never hardcode tool slugs or argument shapes
  • Verify Flowiseai connection is ACTIVE via RUBE_MANAGE_CONNECTIONS before execution
  • Pass an explicit memory object (even empty) to RUBE_MULTI_EXECUTE_TOOL calls
  • Reuse session IDs within a workflow; generate new sessions for new workflows
  • Respect pagination tokens and fetch all result pages when present
  • Use RUBE_GET_TOOL_SCHEMAS when a tool returns a schemaRef for full schema details

Example use cases

  • Discover and run a Flowiseai model transformer using the live schema returned by RUBE_SEARCH_TOOLS
  • Batch-run dataset preparation and pipeline steps through RUBE_REMOTE_WORKBENCH and run_composio_tool()
  • Embed Flowiseai operations into an agent that checks connection status then executes tools in sequence
  • Create CI hooks that verify connection and execute validation workflows before deployments
  • Automate tool discovery and execution in pipelines where tool arguments or names may change frequently

FAQ

What must I do before executing any Flowiseai tool?

Always call RUBE_SEARCH_TOOLS to fetch current tool slugs and schemas, then confirm the Flowiseai connection is ACTIVE with RUBE_MANAGE_CONNECTIONS.

Is memory required for RUBE_MULTI_EXECUTE_TOOL?

Yes. Always include a memory parameter (it can be an empty object) when calling RUBE_MULTI_EXECUTE_TOOL to ensure consistent execution behavior.