Sendbird AI Chabot Automation

What This Skill Does

This skill automates Sendbird AI Chabot operations using the Composio Sendbird AI Chabot toolkit via Rube MCP. It enables users to programmatically manage and interact with Sendbird AI Chatbots. This is useful for developers and businesses looking to automate chatbot interactions and workflows.

When to Use

• Automate chatbot training data updates.
• Retrieve chatbot conversation logs.
• Monitor chatbot performance metrics.
• Trigger automated chatbot responses.
• Manage chatbot user interactions.
• Integrate chatbots with other systems.

Key Features

Uses Rube MCP for tool discovery and execution. Requires an active Sendbird AI Chabot connection. Employs RUBE_SEARCH_TOOLS to find available tools. Uses RUBE_MANAGE_CONNECTIONS to manage connections. Executes tools via RUBE_MULTI_EXECUTE_TOOL. Provides a structured workflow for chatbot automation.

Manual Installation

Prerequisites

• Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
• Active Sendbird AI Chabot connection via RUBE_MANAGE_CONNECTIONS with toolkit sendbird_ai_chabot.
• 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 sendbird_ai_chabot.
• 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: "Sendbird AI Chabot 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 Sendbird AI Chabot task"}] session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS toolkits: ["sendbird_ai_chabot"] 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

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

Toolkit docs: composio.dev/toolkits/sendbird_ai_chabot

Prerequisites

• Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
• Active Sendbird AI Chabot connection via RUBE_MANAGE_CONNECTIONS with toolkit sendbird_ai_chabot.
• 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 sendbird_ai_chabot.
• 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: "Sendbird AI Chabot 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 Sendbird AI Chabot task"}] session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS toolkits: ["sendbird_ai_chabot"] 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