What is required to use wit-ai-automation?

Rube MCP must be connected, Wit AI must be connected via RUBE_MANAGE_CONNECTIONS with toolkit wit_ai, and you must always call RUBE_SEARCH_TOOLS first to fetch current tool schemas.

No API keys are required. You connect through the Rube MCP endpoint and use the toolkit-driven tools and schemas.

How do I discover tools and their schemas?

Use RUBE_SEARCH_TOOLS with a Wit AI use case to retrieve tool slugs, input schemas, recommended execution plans, and known pitfalls.

wit-ai-automation

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Wit AI Automation via Rube MCP

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

Toolkit docs: composio.dev/toolkits/wit_ai

Prerequisites

Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
Active Wit AI connection via RUBE_MANAGE_CONNECTIONS with toolkit wit_ai
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.

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

Tool Discovery

Always discover available tools before executing workflows:

RUBE_SEARCH_TOOLS
queries: [{use_case: "Wit AI 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 Wit AI task"}]
session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS
toolkits: ["wit_ai"]
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 Wit AI-specific use case
Connect	`RUBE_MANAGE_CONNECTIONS` with toolkit `wit_ai`
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

Source

git clone https://github.com/ComposioHQ/awesome-claude-skills/blob/master/composio-skills/wit-ai-automation/SKILL.mdView on GitHub

Overview

Automate Wit AI operations through Composio's Wit AI toolkit via Rube MCP. It relies on always fetching current tool schemas with RUBE_SEARCH_TOOLS before running workflows, ensuring slugs and inputs stay up to date. This makes Wit AI automation reliable, repeatable, and scalable across tasks.

How This Skill Works

Tools are discovered via RUBE_SEARCH_TOOLS to pull current tool slugs and schemas. You then verify the Wit AI connection with RUBE_MANAGE_CONNECTIONS, ensure the session is ACTIVE, and execute the chosen tools using RUBE_MULTI_EXECUTE_TOOL with memory and the schema-backed arguments.

When to Use It

When you need to automate repetitive Wit AI tasks without manually updating tool slugs or inputs.
When tool schemas may change and you must fetch the latest slugs before execution.
When establishing a new Wit AI integration and validating an ACTIVE connection.
When running a sequence of Wit AI operations in a single session to preserve context.
When handling complex workflows requiring stepwise discovery and execution with memory.

Quick Start

Step 1: Get Rube MCP by adding https://rube.app/mcp as an MCP server in your client configuration.
Step 2: Verify availability with RUBE_SEARCH_TOOLS (tools discovery) and fetch current schemas.
Step 3: Manage connection with RUBE_MANAGE_CONNECTIONS (toolkit: wit_ai) and run RUBE_MULTI_EXECUTE_TOOL with the discovered tool slug and memory.

Best Practices

Always run RUBE_SEARCH_TOOLS first to pull current tool schemas.
Verify RUBE_MANAGE_CONNECTIONS shows ACTIVE before execution.
Use exact field names and types from the search results.
Include memory: {} in every RUBE_MULTI_EXECUTE_TOOL call.
Reuse session IDs within a workflow; create new ones for new workflows.

Example Use Cases

Automate a Wit AI sentiment analysis flow by discovering the appropriate tool slug via RUBE_SEARCH_TOOLS and executing it with RUBE_MULTI_EXECUTE_TOOL.
Run a batch Wit AI data extraction task by maintaining a session and reusing it across multiple tool executions.
Connect a new Wit AI account, verify ACTIVE status, and perform a test workflow to validate integration.
Process multiple Wit AI translation steps by fetching latest schemas and chaining TOOL_SLUG-based executions.
End-to-end Wit AI operation from discovery to execution in a single workflow, handling pagination tokens as needed.

Frequently Asked Questions

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