Scrapegraph AI Automation

What This Skill Does

This skill automates Scrapegraph AI operations using Composio's toolkit via Rube MCP. It's designed for users who need to programmatically interact with Scrapegraph AI for web scraping and data extraction workflows. The skill ensures proper setup, tool discovery, and execution while adhering to schema compliance.

When to Use

• Automate data extraction from websites.
• Integrate web scraping into existing workflows.
• Dynamically adjust scraping parameters.
• Monitor website content changes.
• Orchestrate complex scraping tasks.
• Build custom web scraping solutions.

Key Features

• Automates Scrapegraph AI via Rube MCP.
• Discovers available tools and schemas.
• Manages Scrapegraph AI connections.
• Executes tools with schema validation.
• Provides a structured workflow pattern.
• Handles connection and schema pitfalls.

Manual Installation

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

Toolkit docs: composio.dev/toolkits/scrapegraph_ai

Prerequisites

Rube MCP must be connected (RUBE_SEARCH_TOOLS available) Active Scrapegraph AI connection via RUBE_MANAGE_CONNECTIONS with toolkit scrapegraph_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 scrapegraph_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: "Scrapegraph 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 Scrapegraph AI task"}] session: {id: "existing_session_id"}

Step 2: Check Connection

RUBE_MANAGE_CONNECTIONS toolkits: ["scrapegraph_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