What does the `assess_business_automation` tool require?
It requires the industry, pain points, team size, and current tools. It returns a readiness score (0–100) with personalized automation recommendations.
@Ronnie-Nutrition
Basic information
Assess your business's AI automation readiness across 20 industries. Get a personalized score, specific automation recommendations, and time/revenue impact estimates.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"easyaiflows": {
"command": "npx",
"args": [
"easyaiflows-mcp-server"
]
}
}
}Assess a business's AI automation readiness based on their industry and pain points. Returns a personalized automation score, specific recommendations, and next steps.
Get real examples of AI automations for a specific industry, including what they do, time saved, and revenue impact.
Easyaiflows Automation Assessment is an MCP server that helps AI assistants evaluate business automation readiness and deliver industry-specific recommendations. It is intended for users seeking to identify automation opportunities across small and local businesses.
The server exposes two tools: assess_business_automation and get_automation_examples. Invoke them via an MCP client. No specific install or config commands are mentioned.
It requires the industry, pain points, team size, and current tools. It returns a readiness score (0–100) with personalized automation recommendations.
It returns three proven automations for any of the 20 supported industries, along with time saved and revenue impact for each.
Twenty industries: Dentists, Restaurants, HVAC, Real Estate, Fitness Studios, Barbershops, Nail Salons, Med Spas, Chiropractors, Insurance Agents, Mortgage Brokers, Photographers, Event Planners, Cleaning Services, Landscapers, Auto Repair, Pet Groomers, Daycares, Churches, and Nonprofits.
The README does not list any specific dependencies, runtime requirements, or transport/auth details.
The server uses input provided at runtime (industry, pain points, etc.) and returns generated recommendations. No external database or user data persistence is mentioned.

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