According to monitoring by Beating, customer service AI platform Parloa has launched the Agent Skills feature based on the Model Context Protocol (MCP). Agent Skills transform system integrations that previously required programmers to write code and were tied to specific conversation flows into independent 'plugin skills.' This allows business teams to configure integrations with CRM, booking engines, ticketing systems, and more on the management platform without coding, reducing the development and deployment cycle from 4-8 weeks to just hours. Traditional API integrations are not designed for the AI agent ecosystem, often facing high engineering development costs and the risk of crashes due to interface adjustments. Parloa introduces MCP as a structured tool definition layer, enabling large models to natively understand and interact, improving the reliability of tool selection and command adherence. Agent Skills operate on deterministic logic, featuring error recovery and automatic retry mechanisms. Business teams can configure multiple tool integration chains through the platform and define Success Conditions for specific tasks to track real business outputs, no longer limited to monitoring underlying network request events. AI agents can autonomously select and execute corresponding skills in conversations based on user intent. Real-world data shows that after using Agent Skills, the average handling time for AI customer service has decreased by 67 seconds, routing reliability in multi-tool environments has improved by 20%, and the quality of context transfer during phone handoffs has improved by 39%. Any system with an API interface can be quickly packaged as Agent Skills.